The R Project SVN – R – Diff – /trunk/tests/Examples/stats-Ex.Rout.save

Rev 63205		Rev 63207
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1		1
2	`R Under development (unstable) (2013-07-06 r63204) -- "Unsuffered Consequences"`	2	`R Under development (unstable) (2013-07-07 r63206) -- "Unsuffered Consequences"`
3	`Copyright (C) 2013 The R Foundation for Statistical Computing`	3	`Copyright (C) 2013 The R Foundation for Statistical Computing`
4	`Platform: x86_64-apple-darwin12.4.0/x86_64 (64-bit)`	4	`Platform: x86_64-unknown-linux-gnu (64-bit)`
5		5
6	`R is free software and comes with ABSOLUTELY NO WARRANTY.`	6	`R is free software and comes with ABSOLUTELY NO WARRANTY.`
7	`You are welcome to redistribute it under certain conditions.`	7	`You are welcome to redistribute it under certain conditions.`
8	`Type 'license()' or 'licence()' for distribution details.`	8	`Type 'license()' or 'licence()' for distribution details.`
9		9
Line 912...		Line 912...
912	`Estimate Std. Error t value Pr(>\|t\|)`	912	`Estimate Std. Error t value Pr(>\|t\|)`
913	`Asym 94.1282 8.4030 11.202 0.001525 **`	913	`Asym 94.1282 8.4030 11.202 0.001525 **`
914	`resp0 -8.2508 1.2261 -6.729 0.006700 **`	914	`resp0 -8.2508 1.2261 -6.729 0.006700 **`
915	`lrc -3.2176 0.1386 -23.218 0.000175 ***`	915	`lrc -3.2176 0.1386 -23.218 0.000175 ***`
916	`---`	916	`---`
917	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	917	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
918		918
919	`Residual standard error: 0.7493 on 3 degrees of freedom`	919	`Residual standard error: 0.7493 on 3 degrees of freedom`
920		920
921	`> ## Don't show:`	921	`> ## Don't show:`
922	`> require(graphics)`	922	`> require(graphics)`
Line 997...		Line 997...
997	`Estimate Std. Error t value Pr(>\|t\|)`	997	`Estimate Std. Error t value Pr(>\|t\|)`
998	`Asym 38.1398 0.9164 41.620 1.99e-06 ***`	998	`Asym 38.1398 0.9164 41.620 1.99e-06 ***`
999	`lrc -4.3806 0.2042 -21.457 2.79e-05 ***`	999	`lrc -4.3806 0.2042 -21.457 2.79e-05 ***`
1000	`c0 51.2232 11.6698 4.389 0.0118 *`	1000	`c0 51.2232 11.6698 4.389 0.0118 *`
1001	`---`	1001	`---`
1002	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1002	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1003		1003
1004	`Residual standard error: 1.663 on 4 degrees of freedom`	1004	`Residual standard error: 1.663 on 4 degrees of freedom`
1005		1005
1006	`> ## Don't show:`	1006	`> ## Don't show:`
1007	`> require(graphics)`	1007	`> require(graphics)`
Line 1120...		Line 1120...
1120	`A1 2.0293 0.1099 18.464 3.39e-07 ***`	1120	`A1 2.0293 0.1099 18.464 3.39e-07 ***`
1121	`lrc1 0.5794 0.1247 4.648 0.00235 **`	1121	`lrc1 0.5794 0.1247 4.648 0.00235 **`
1122	`A2 0.1915 0.1106 1.731 0.12698`	1122	`A2 0.1915 0.1106 1.731 0.12698`
1123	`lrc2 -1.7878 0.7871 -2.271 0.05737 .`	1123	`lrc2 -1.7878 0.7871 -2.271 0.05737 .`
1124	`---`	1124	`---`
1125	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1125	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1126		1126
1127	`Residual standard error: 0.04103 on 7 degrees of freedom`	1127	`Residual standard error: 0.04103 on 7 degrees of freedom`
1128		1128
1129	`> ## Don't show:`	1129	`> ## Don't show:`
1130	`> require(graphics)`	1130	`> require(graphics)`
Line 1207...		Line 1207...
1207	`Estimate Std. Error t value Pr(>\|t\|)`	1207	`Estimate Std. Error t value Pr(>\|t\|)`
1208	`lKe -2.9196 0.1709 -17.085 1.40e-07 ***`	1208	`lKe -2.9196 0.1709 -17.085 1.40e-07 ***`
1209	`lKa 0.5752 0.1728 3.328 0.0104 *`	1209	`lKa 0.5752 0.1728 3.328 0.0104 *`
1210	`lCl -3.9159 0.1273 -30.768 1.35e-09 ***`	1210	`lCl -3.9159 0.1273 -30.768 1.35e-09 ***`
1211	`---`	1211	`---`
1212	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1212	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1213		1213
1214	`Residual standard error: 0.732 on 8 degrees of freedom`	1214	`Residual standard error: 0.732 on 8 degrees of freedom`
1215		1215
1216	`>`	1216	`>`
1217	`>`	1217	`>`
Line 1266...		Line 1266...
1266	`A 27.453 6.601 4.159 0.003169 **`	1266	`A 27.453 6.601 4.159 0.003169 **`
1267	`B 348.971 57.899 6.027 0.000314 ***`	1267	`B 348.971 57.899 6.027 0.000314 ***`
1268	`xmid 19.391 2.194 8.836 2.12e-05 ***`	1268	`xmid 19.391 2.194 8.836 2.12e-05 ***`
1269	`scal 6.673 1.002 6.662 0.000159 ***`	1269	`scal 6.673 1.002 6.662 0.000159 ***`
1270	`---`	1270	`---`
1271	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1271	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1272		1272
1273	`Residual standard error: 2.351 on 8 degrees of freedom`	1273	`Residual standard error: 2.351 on 8 degrees of freedom`
1274		1274
1275	`> ## Don't show:`	1275	`> ## Don't show:`
1276	`> require(graphics)`	1276	`> require(graphics)`
Line 1361...		Line 1361...
1361	`Estimate Std. Error t value Pr(>\|t\|)`	1361	`Estimate Std. Error t value Pr(>\|t\|)`
1362	`Asym 4.60333 0.65321 7.047 8.71e-06 ***`	1362	`Asym 4.60333 0.65321 7.047 8.71e-06 ***`
1363	`b2 2.27134 0.14373 15.803 7.24e-10 ***`	1363	`b2 2.27134 0.14373 15.803 7.24e-10 ***`
1364	`b3 0.71647 0.02206 32.475 7.85e-14 ***`	1364	`b3 0.71647 0.02206 32.475 7.85e-14 ***`
1365	`---`	1365	`---`
1366	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1366	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1367		1367
1368	`Residual standard error: 0.02684 on 13 degrees of freedom`	1368	`Residual standard error: 0.02684 on 13 degrees of freedom`
1369		1369
1370	`>`	1370	`>`
1371	`>`	1371	`>`
Line 1457...		Line 1457...
1457	`Parameters:`	1457	`Parameters:`
1458	`Estimate Std. Error t value Pr(>\|t\|)`	1458	`Estimate Std. Error t value Pr(>\|t\|)`
1459	`Vm 2.127e+02 6.947e+00 30.615 3.24e-11 ***`	1459	`Vm 2.127e+02 6.947e+00 30.615 3.24e-11 ***`
1460	`K 6.412e-02 8.281e-03 7.743 1.57e-05 ***`	1460	`K 6.412e-02 8.281e-03 7.743 1.57e-05 ***`
1461	`---`	1461	`---`
1462	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1462	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1463		1463
1464	`Residual standard error: 10.93 on 10 degrees of freedom`	1464	`Residual standard error: 10.93 on 10 degrees of freedom`
1465		1465
1466	`> ## Alternative call using the subset argument`	1466	`> ## Alternative call using the subset argument`
1467	`> fm2 <- nls(rate ~ SSmicmen(conc, Vm, K), data = Puromycin,`	1467	`> fm2 <- nls(rate ~ SSmicmen(conc, Vm, K), data = Puromycin,`
Line 1473...		Line 1473...
1473	`Parameters:`	1473	`Parameters:`
1474	`Estimate Std. Error t value Pr(>\|t\|)`	1474	`Estimate Std. Error t value Pr(>\|t\|)`
1475	`Vm 2.127e+02 6.947e+00 30.615 3.24e-11 ***`	1475	`Vm 2.127e+02 6.947e+00 30.615 3.24e-11 ***`
1476	`K 6.412e-02 8.281e-03 7.743 1.57e-05 ***`	1476	`K 6.412e-02 8.281e-03 7.743 1.57e-05 ***`
1477	`---`	1477	`---`
1478	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1478	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1479		1479
1480	`Residual standard error: 10.93 on 10 degrees of freedom`	1480	`Residual standard error: 10.93 on 10 degrees of freedom`
1481		1481
1482	`> ## Don't show:`	1482	`> ## Don't show:`
1483	`> require(graphics)`	1483	`> require(graphics)`
Line 1552...		Line 1552...
1552	`Asym 158.5012 1.1769 134.67 3.28e-13 ***`	1552	`Asym 158.5012 1.1769 134.67 3.28e-13 ***`
1553	`Drop 110.9971 2.6330 42.16 1.10e-09 ***`	1553	`Drop 110.9971 2.6330 42.16 1.10e-09 ***`
1554	`lrc -5.9934 0.3733 -16.05 8.83e-07 ***`	1554	`lrc -5.9934 0.3733 -16.05 8.83e-07 ***`
1555	`pwr 2.6461 0.1613 16.41 7.62e-07 ***`	1555	`pwr 2.6461 0.1613 16.41 7.62e-07 ***`
1556	`---`	1556	`---`
1557	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1557	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1558		1558
1559	`Residual standard error: 2.061 on 7 degrees of freedom`	1559	`Residual standard error: 2.061 on 7 degrees of freedom`
1560		1560
1561	`>`	1561	`>`
1562	`>`	1562	`>`
Line 1729...		Line 1729...
1729	`Df Sum Sq Mean Sq F value Pr(>F)`	1729	`Df Sum Sq Mean Sq F value Pr(>F)`
1730	`wool 1 451 450.7 3.339 0.07361 .`	1730	`wool 1 451 450.7 3.339 0.07361 .`
1731	`tension 2 2034 1017.1 7.537 0.00138 **`	1731	`tension 2 2034 1017.1 7.537 0.00138 **`
1732	`Residuals 50 6748 135.0`	1732	`Residuals 50 6748 135.0`
1733	`---`	1733	`---`
1734	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1734	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1735	`> TukeyHSD(fm1, "tension", ordered = TRUE)`	1735	`> TukeyHSD(fm1, "tension", ordered = TRUE)`
1736	`Tukey multiple comparisons of means`	1736	`Tukey multiple comparisons of means`
1737	`95% family-wise confidence level`	1737	`95% family-wise confidence level`
1738	`factor levels have been ordered`	1738	`factor levels have been ordered`
1739		1739
Line 1988...		Line 1988...
1988	`Examination 1 53 2158 190 1.03 0.3155`	1988	`Examination 1 53 2158 190 1.03 0.3155`
1989	`Education 1 1163 3268 209 22.64 2.4e-05 ***`	1989	`Education 1 1163 3268 209 22.64 2.4e-05 ***`
1990	`Catholic 1 448 2553 198 8.72 0.0052 **`	1990	`Catholic 1 448 2553 198 8.72 0.0052 **`
1991	`Infant.Mortality 1 409 2514 197 7.96 0.0073 **`	1991	`Infant.Mortality 1 409 2514 197 7.96 0.0073 **`
1992	`---`	1992	`---`
1993	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	1993	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
1994	`>`	1994	`>`
1995	`> ## following example(glm)`	1995	`> ## following example(glm)`
1996	`> ## Don't show:`	1996	`> ## Don't show:`
1997	`> example(glm, echo = FALSE)`	1997	`> example(glm, echo = FALSE)`
1998	`treatment outcome counts`	1998	`treatment outcome counts`
Line 2014...		Line 2014...
2014	`Df Deviance AIC LRT Pr(>Chi)`	2014	`Df Deviance AIC LRT Pr(>Chi)`
2015	`<none> 5.13 56.8`	2015	`<none> 5.13 56.8`
2016	`outcome 2 10.58 58.2 5.45 0.065 .`	2016	`outcome 2 10.58 58.2 5.45 0.065 .`
2017	`treatment 2 5.13 52.8 0.00 1.000`	2017	`treatment 2 5.13 52.8 0.00 1.000`
2018	`---`	2018	`---`
2019	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2019	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2020	`> drop1(glm.D93, test = "F")`	2020	`> drop1(glm.D93, test = "F")`
2021	`Warning in drop1.glm(glm.D93, test = "F") :`	2021	`Warning in drop1.glm(glm.D93, test = "F") :`
2022	`F test assumes 'quasipoisson' family`	2022	`F test assumes 'quasipoisson' family`
2023	`Single term deletions`	2023	`Single term deletions`
2024		2024
Line 2532...		Line 2532...
2532	`Df Deviance Resid. Df Resid. Dev Pr(>Chi)`	2532	`Df Deviance Resid. Df Resid. Dev Pr(>Chi)`
2533	`NULL 8 10.5814`	2533	`NULL 8 10.5814`
2534	`outcome 2 5.4523 6 5.1291 0.06547 .`	2534	`outcome 2 5.4523 6 5.1291 0.06547 .`
2535	`treatment 2 0.0000 4 5.1291 1.00000`	2535	`treatment 2 0.0000 4 5.1291 1.00000`
2536	`---`	2536	`---`
2537	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2537	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2538	`> glm.D93a <-`	2538	`> glm.D93a <-`
2539	`+ update(glm.D93, ~treatment*outcome) # equivalent to Pearson Chi-square`	2539	`+ update(glm.D93, ~treatment*outcome) # equivalent to Pearson Chi-square`
2540	`> anova(glm.D93, glm.D93a, test = "Rao")`	2540	`> anova(glm.D93, glm.D93a, test = "Rao")`
2541	`Analysis of Deviance Table`	2541	`Analysis of Deviance Table`
2542		2542
Line 2572...		Line 2572...
2572	`pop75 1 53.34 53.343 3.6889 0.0611255 .`	2572	`pop75 1 53.34 53.343 3.6889 0.0611255 .`
2573	`dpi 1 12.40 12.401 0.8576 0.3593551`	2573	`dpi 1 12.40 12.401 0.8576 0.3593551`
2574	`ddpi 1 63.05 63.054 4.3605 0.0424711 *`	2574	`ddpi 1 63.05 63.054 4.3605 0.0424711 *`
2575	`Residuals 45 650.71 14.460`	2575	`Residuals 45 650.71 14.460`
2576	`---`	2576	`---`
2577	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2577	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2578	`>`	2578	`>`
2579	`> ## same effect via separate models`	2579	`> ## same effect via separate models`
2580	`> fit0 <- lm(sr ~ 1, data = LifeCycleSavings)`	2580	`> fit0 <- lm(sr ~ 1, data = LifeCycleSavings)`
2581	`> fit1 <- update(fit0, . ~ . + pop15)`	2581	`> fit1 <- update(fit0, . ~ . + pop15)`
2582	`> fit2 <- update(fit1, . ~ . + pop75)`	2582	`> fit2 <- update(fit1, . ~ . + pop75)`
Line 2595...		Line 2595...
2595	`2 48 779.51 1 204.118 14.1157 0.0004922 ***`	2595	`2 48 779.51 1 204.118 14.1157 0.0004922 ***`
2596	`3 47 726.17 1 53.343 3.6889 0.0611255 .`	2596	`3 47 726.17 1 53.343 3.6889 0.0611255 .`
2597	`4 46 713.77 1 12.401 0.8576 0.3593551`	2597	`4 46 713.77 1 12.401 0.8576 0.3593551`
2598	`5 45 650.71 1 63.054 4.3605 0.0424711 *`	2598	`5 45 650.71 1 63.054 4.3605 0.0424711 *`
2599	`---`	2599	`---`
2600	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2600	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2601	`>`	2601	`>`
2602	`> anova(fit4, fit2, fit0, test = "F") # unconventional order`	2602	`> anova(fit4, fit2, fit0, test = "F") # unconventional order`
2603	`Analysis of Variance Table`	2603	`Analysis of Variance Table`
2604		2604
2605	`Model 1: sr ~ pop15 + pop75 + dpi + ddpi`	2605	`Model 1: sr ~ pop15 + pop75 + dpi + ddpi`
Line 2608...		Line 2608...
2608	`Res.Df RSS Df Sum of Sq F Pr(>F)`	2608	`Res.Df RSS Df Sum of Sq F Pr(>F)`
2609	`1 45 650.71`	2609	`1 45 650.71`
2610	`2 47 726.17 -2 -75.455 2.6090 0.0847088 .`	2610	`2 47 726.17 -2 -75.455 2.6090 0.0847088 .`
2611	`3 49 983.63 -2 -257.460 8.9023 0.0005527 ***`	2611	`3 49 983.63 -2 -257.460 8.9023 0.0005527 ***`
2612	`---`	2612	`---`
2613	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2613	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2614	`>`	2614	`>`
2615	`>`	2615	`>`
2616	`>`	2616	`>`
2617	`> cleanEx()`	2617	`> cleanEx()`
2618	`> nameEx("anova.mlm")`	2618	`> nameEx("anova.mlm")`
Line 2696...		Line 2696...
2696		2696
2697	`Res.Df Df Gen.var. Pillai approx F num Df den Df Pr(>F)`	2697	`Res.Df Df Gen.var. Pillai approx F num Df den Df Pr(>F)`
2698	`1 9 1249.6`	2698	`1 9 1249.6`
2699	`2 10 1 2013.2 0.9456 17.381 5 5 0.003534 **`	2699	`2 10 1 2013.2 0.9456 17.381 5 5 0.003534 **`
2700	`---`	2700	`---`
2701	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2701	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2702	`>`	2702	`>`
2703	`> ## Assuming sphericity`	2703	`> ## Assuming sphericity`
2704	`> anova(mlmfit, mlmfit0, X = ~1, test = "Spherical")`	2704	`> anova(mlmfit, mlmfit0, X = ~1, test = "Spherical")`
2705	`Analysis of Variance Table`	2705	`Analysis of Variance Table`
2706		2706
Line 2987...		Line 2987...
2987	`Df Sum Sq Mean Sq F value Pr(>F)`	2987	`Df Sum Sq Mean Sq F value Pr(>F)`
2988	`N 1 189.28 189.28 12.259 0.00437 **`	2988	`N 1 189.28 189.28 12.259 0.00437 **`
2989	`P 1 8.40 8.40 0.544 0.47490`	2989	`P 1 8.40 8.40 0.544 0.47490`
2990	`K 1 95.20 95.20 6.166 0.02880 *`	2990	`K 1 95.20 95.20 6.166 0.02880 *`
2991	`N:P 1 21.28 21.28 1.378 0.26317`	2991	`N:P 1 21.28 21.28 1.378 0.26317`
2992	`N:K 1 33.13 33.13 2.146 0.16865`	2992	`N:K 1 33.14 33.14 2.146 0.16865`
2993	`P:K 1 0.48 0.48 0.031 0.86275`	2993	`P:K 1 0.48 0.48 0.031 0.86275`
2994	`Residuals 12 185.29 15.44`	2994	`Residuals 12 185.29 15.44`
2995	`---`	2995	`---`
2996	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	2996	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
2997	`> options(op) # reset to previous`	2997	`> options(op) # reset to previous`
2998	`>`	2998	`>`
2999	`>`	2999	`>`
3000	`>`	3000	`>`
3001	`> base::options(contrasts = c(unordered = "contr.treatment",ordered = "contr.poly"))`	3001	`> base::options(contrasts = c(unordered = "contr.treatment",ordered = "contr.poly"))`
Line 3696...		Line 3696...
3696	`>`	3696	`>`
3697	`>`	3697	`>`
3698	`> graphics::par(get("par.postscript", pos = 'CheckExEnv'))`	3698	`> graphics::par(get("par.postscript", pos = 'CheckExEnv'))`
3699	`> cleanEx()`	3699	`> cleanEx()`
3700		3700
3701	`detaching 'package:cluster'`	3701	`detaching ‘package:cluster’`
3702		3702
3703	`> nameEx("asOneSidedFormula")`	3703	`> nameEx("asOneSidedFormula")`
3704	`> ### * asOneSidedFormula`	3704	`> ### * asOneSidedFormula`
3705	`>`	3705	`>`
3706	`> flush(stderr()); flush(stdout())`	3706	`> flush(stderr()); flush(stdout())`
Line 3712...		Line 3712...
3712	`>`	3712	`>`
3713	`> ### ** Examples`	3713	`> ### ** Examples`
3714	`>`	3714	`>`
3715	`> asOneSidedFormula("age")`	3715	`> asOneSidedFormula("age")`
3716	`~age`	3716	`~age`
3717	`<environment: 0x7f9342c1cd88>`	3717	`<environment: 0x4fbcac8>`
3718	`> asOneSidedFormula(~ age)`	3718	`> asOneSidedFormula(~ age)`
3719	`~age`	3719	`~age`
3720	`>`	3720	`>`
3721	`>`	3721	`>`
3722	`>`	3722	`>`
Line 4030...		Line 4030...
4030	`x 5.524412 1.255354 4.401 0.000516 ***`	4030	`x 5.524412 1.255354 4.401 0.000516 ***`
4031	`I(x^2) -0.542292 0.138460 -3.917 0.001374 **`	4031	`I(x^2) -0.542292 0.138460 -3.917 0.001374 **`
4032	`I(x^3) 0.020905 0.004372 4.782 0.000242 ***`	4032	`I(x^3) 0.020905 0.004372 4.782 0.000242 ***`
4033	`I((x - 10)^2) NA NA NA NA`	4033	`I((x - 10)^2) NA NA NA NA`
4034	`---`	4034	`---`
4035	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	4035	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
4036		4036
4037	`Residual standard error: 2.838 on 15 degrees of freedom`	4037	`Residual standard error: 2.838 on 15 degrees of freedom`
4038	`Multiple R-squared: 0.9702, Adjusted R-squared: 0.9643`	4038	`Multiple R-squared: 0.9702, Adjusted R-squared: 0.9643`
4039	`F-statistic: 163 on 3 and 15 DF, p-value: 1.14e-11`	4039	`F-statistic: 163 on 3 and 15 DF, p-value: 1.14e-11`
4040		4040
Line 4663...		Line 4663...
4663	`Armed.Forces . . 1`	4663	`Armed.Forces . . 1`
4664	`Population B B , . 1`	4664	`Population B B , . 1`
4665	`Year B B , . B 1`	4665	`Year B B , . B 1`
4666	`Employed B B . . B B 1`	4666	`Employed B B . . B B 1`
4667	`attr(,"legend")`	4667	`attr(,"legend")`
4668	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	4668	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
4669	`>`	4669	`>`
4670	`> ## Spearman's rho and Kendall's tau`	4670	`> ## Spearman's rho and Kendall's tau`
4671	`> symnum(clS <- cor(longley, method = "spearman"))`	4671	`> symnum(clS <- cor(longley, method = "spearman"))`
4672	`GNP. GNP U A P Y E`	4672	`GNP. GNP U A P Y E`
4673	`GNP.deflator 1`	4673	`GNP.deflator 1`
Line 4676...		Line 4676...
4676	`Armed.Forces . 1`	4676	`Armed.Forces . 1`
4677	`Population B B , 1`	4677	`Population B B , 1`
4678	`Year B B , 1 1`	4678	`Year B B , 1 1`
4679	`Employed B B . B B 1`	4679	`Employed B B . B B 1`
4680	`attr(,"legend")`	4680	`attr(,"legend")`
4681	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	4681	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
4682	`> symnum(clK <- cor(longley, method = "kendall"))`	4682	`> symnum(clK <- cor(longley, method = "kendall"))`
4683	`GNP. GNP U A P Y E`	4683	`GNP. GNP U A P Y E`
4684	`GNP.deflator 1`	4684	`GNP.deflator 1`
4685	`GNP B 1`	4685	`GNP B 1`
4686	`Unemployed . . 1`	4686	`Unemployed . . 1`
4687	`Armed.Forces 1`	4687	`Armed.Forces 1`
4688	`Population B B . 1`	4688	`Population B B . 1`
4689	`Year B B . 1 1`	4689	`Year B B . 1 1`
4690	`Employed * * . + + 1`	4690	`Employed * * . + + 1`
4691	`attr(,"legend")`	4691	`attr(,"legend")`
4692	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	4692	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
4693	`> ## How much do they differ?`	4693	`> ## How much do they differ?`
4694	`> i <- lower.tri(Cl)`	4694	`> i <- lower.tri(Cl)`
4695	`> cor(cbind(P = Cl[i], S = clS[i], K = clK[i]))`	4695	`> cor(cbind(P = Cl[i], S = clS[i], K = clK[i]))`
4696	`P S K`	4696	`P S K`
4697	`P 1.0000000 0.9802390 0.9572562`	4697	`P 1.0000000 0.9802390 0.9572562`
Line 4713...		Line 4713...
4713	`r <- V`	4713	`r <- V`
4714	`r[] <- Is * V * rep(Is, each = p)`	4714	`r[] <- Is * V * rep(Is, each = p)`
4715	`r[cbind(1L:p, 1L:p)] <- 1`	4715	`r[cbind(1L:p, 1L:p)] <- 1`
4716	`r`	4716	`r`
4717	`}`	4717	`}`
4718	`<bytecode: 0x7f934795c078>`	4718	`<bytecode: 0x7bd76c0>`
4719	`<environment: namespace:stats>`	4719	`<environment: namespace:stats>`
4720	`> stopifnot(all.equal(Cl, cov2cor(cov(longley))),`	4720	`> stopifnot(all.equal(Cl, cov2cor(cov(longley))),`
4721	`+ all.equal(cor(longley, method = "kendall"),`	4721	`+ all.equal(cor(longley, method = "kendall"),`
4722	`+ cov2cor(cov(longley, method = "kendall"))))`	4722	`+ cov2cor(cov(longley, method = "kendall"))))`
4723	`>`	4723	`>`
Line 4758...		Line 4758...
4758	`Exmntn . . 1`	4758	`Exmntn . . 1`
4759	`Eductn . . . 1`	4759	`Eductn . . . 1`
4760	`Cathlc . 1`	4760	`Cathlc . 1`
4761	`Infn.M 1`	4761	`Infn.M 1`
4762	`attr(,"legend")`	4762	`attr(,"legend")`
4763	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	4763	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
4764	`> symnum(Rp <- cor(swM, method = "kendall", use = "pairwise"))`	4764	`> symnum(Rp <- cor(swM, method = "kendall", use = "pairwise"))`
4765	`F A Ex Ed C I`	4765	`F A Ex Ed C I`
4766	`Frtlty 1`	4766	`Frtlty 1`
4767	`Agrclt 1`	4767	`Agrclt 1`
4768	`Exmntn . . 1`	4768	`Exmntn . . 1`
4769	`Eductn . . . 1`	4769	`Eductn . . . 1`
4770	`Cathlc . 1`	4770	`Cathlc . 1`
4771	`Infn.M . 1`	4771	`Infn.M . 1`
4772	`attr(,"legend")`	4772	`attr(,"legend")`
4773	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	4773	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
4774	`> symnum(R. <- cor(swiss, method = "kendall"))`	4774	`> symnum(R. <- cor(swiss, method = "kendall"))`
4775	`F A Ex Ed C I`	4775	`F A Ex Ed C I`
4776	`Fertility 1`	4776	`Fertility 1`
4777	`Agriculture 1`	4777	`Agriculture 1`
4778	`Examination . . 1`	4778	`Examination . . 1`
4779	`Education . . . 1`	4779	`Education . . . 1`
4780	`Catholic . 1`	4780	`Catholic . 1`
4781	`Infant.Mortality . 1`	4781	`Infant.Mortality . 1`
4782	`attr(,"legend")`	4782	`attr(,"legend")`
4783	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	4783	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
4784	`>`	4784	`>`
4785	`> ## "pairwise" is closer componentwise,`	4785	`> ## "pairwise" is closer componentwise,`
4786	`> summary(abs(c(1 - Rp/R.)))`	4786	`> summary(abs(c(1 - Rp/R.)))`
4787	`Min. 1st Qu. Median Mean 3rd Qu. Max.`	4787	`Min. 1st Qu. Median Mean 3rd Qu. Max.`
4788	`0.00000 0.00000 0.04481 0.09573 0.15210 0.53940`	4788	`0.00000 0.00000 0.04481 0.09573 0.15210 0.53940`
Line 6397...		Line 6397...
6397	`> (fit <- aov(Yield ~ ABC + Error(Block), data = aovdat))`	6397	`> (fit <- aov(Yield ~ ABC + Error(Block), data = aovdat))`
6398		6398
6399	`Call:`	6399	`Call:`
6400	`aov(formula = Yield ~ A * B * C + Error(Block), data = aovdat)`	6400	`aov(formula = Yield ~ A * B * C + Error(Block), data = aovdat)`
6401		6401
6402	`Grand Mean: 291.5937`	6402	`Grand Mean: 291.5938`
6403		6403
6404	`Stratum 1: Block`	6404	`Stratum 1: Block`
6405		6405
6406	`Terms:`	6406	`Terms:`
6407	`A:B A:C B:C A:B:C Residuals`	6407	`A:B A:C B:C A:B:C Residuals`
Line 6416...		Line 6416...
6416	`Terms:`	6416	`Terms:`
6417	`A B C A:B A:C B:C`	6417	`A B C A:B A:C B:C`
6418	`Sum of Squares 3465.28 161170.03 278817.78 28.17 1802.67 11528.17`	6418	`Sum of Squares 3465.28 161170.03 278817.78 28.17 1802.67 11528.17`
6419	`Deg. of Freedom 1 1 1 1 1 1`	6419	`Deg. of Freedom 1 1 1 1 1 1`
6420	`A:B:C Residuals`	6420	`A:B:C Residuals`
6421	`Sum of Squares 45.38 5423.28`	6421	`Sum of Squares 45.37 5423.28`
6422	`Deg. of Freedom 1 17`	6422	`Deg. of Freedom 1 17`
6423		6423
6424	`Residual standard error: 17.86103`	6424	`Residual standard error: 17.86103`
6425	`Estimated effects are balanced`	6425	`Estimated effects are balanced`
6426	`> eff.aovlist(fit)`	6426	`> eff.aovlist(fit)`
Line 7131...		Line 7131...
7131	`> environment(fo)`	7131	`> environment(fo)`
7132	`<environment: R_GlobalEnv>`	7132	`<environment: R_GlobalEnv>`
7133	`> environment(as.formula("y ~ x"))`	7133	`> environment(as.formula("y ~ x"))`
7134	`<environment: R_GlobalEnv>`	7134	`<environment: R_GlobalEnv>`
7135	`> environment(as.formula("y ~ x", env = new.env()))`	7135	`> environment(as.formula("y ~ x", env = new.env()))`
7136	`<environment: 0x7f934a9db600>`	7136	`<environment: 0xaf34e28>`
7137	`>`	7137	`>`
7138	`>`	7138	`>`
7139	`> ## Create a formula for a model with a large number of variables:`	7139	`> ## Create a formula for a model with a large number of variables:`
7140	`> xnam <- paste0("x", 1:25)`	7140	`> xnam <- paste0("x", 1:25)`
7141	`> (fmla <- as.formula(paste("y ~ ", paste(xnam, collapse= "+"))))`	7141	`> (fmla <- as.formula(paste("y ~ ", paste(xnam, collapse= "+"))))`
Line 7572...		Line 7572...
7572	`(Intercept) 49.7711 13.3910 3.717 0.000410 ***`	7572	`(Intercept) 49.7711 13.3910 3.717 0.000410 ***`
7573	`Prewt -0.5655 0.1612 -3.509 0.000803 ***`	7573	`Prewt -0.5655 0.1612 -3.509 0.000803 ***`
7574	`TreatCont -4.0971 1.8935 -2.164 0.033999 *`	7574	`TreatCont -4.0971 1.8935 -2.164 0.033999 *`
7575	`TreatFT 4.5631 2.1333 2.139 0.036035 *`	7575	`TreatFT 4.5631 2.1333 2.139 0.036035 *`
7576	`---`	7576	`---`
7577	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	7577	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
7578		7578
7579	`(Dispersion parameter for gaussian family taken to be 48.69504)`	7579	`(Dispersion parameter for gaussian family taken to be 48.69504)`
7580		7580
7581	`Null deviance: 4525.4 on 71 degrees of freedom`	7581	`Null deviance: 4525.4 on 71 degrees of freedom`
7582	`Residual deviance: 3311.3 on 68 degrees of freedom`	7582	`Residual deviance: 3311.3 on 68 degrees of freedom`
Line 7602...		Line 7602...
7602	`Coefficients:`	7602	`Coefficients:`
7603	`Estimate Std. Error t value Pr(>\|t\|)`	7603	`Estimate Std. Error t value Pr(>\|t\|)`
7604	`(Intercept) -0.0165544 0.0009275 -17.85 4.28e-07 ***`	7604	`(Intercept) -0.0165544 0.0009275 -17.85 4.28e-07 ***`
7605	`log(u) 0.0153431 0.0004150 36.98 2.75e-09 ***`	7605	`log(u) 0.0153431 0.0004150 36.98 2.75e-09 ***`
7606	`---`	7606	`---`
7607	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	7607	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
7608		7608
7609	`(Dispersion parameter for Gamma family taken to be 0.002446059)`	7609	`(Dispersion parameter for Gamma family taken to be 0.002446059)`
7610		7610
7611	`Null deviance: 3.51283 on 8 degrees of freedom`	7611	`Null deviance: 3.51283 on 8 degrees of freedom`
7612	`Residual deviance: 0.01673 on 7 degrees of freedom`	7612	`Residual deviance: 0.01673 on 7 degrees of freedom`
Line 7626...		Line 7626...
7626	`Coefficients:`	7626	`Coefficients:`
7627	`Estimate Std. Error t value Pr(>\|t\|)`	7627	`Estimate Std. Error t value Pr(>\|t\|)`
7628	`(Intercept) -0.0239085 0.0013265 -18.02 4.00e-07 ***`	7628	`(Intercept) -0.0239085 0.0013265 -18.02 4.00e-07 ***`
7629	`log(u) 0.0235992 0.0005768 40.91 1.36e-09 ***`	7629	`log(u) 0.0235992 0.0005768 40.91 1.36e-09 ***`
7630	`---`	7630	`---`
7631	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	7631	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
7632		7632
7633	`(Dispersion parameter for Gamma family taken to be 0.001813354)`	7633	`(Dispersion parameter for Gamma family taken to be 0.001813354)`
7634		7634
7635	`Null deviance: 3.118557 on 8 degrees of freedom`	7635	`Null deviance: 3.118557 on 8 degrees of freedom`
7636	`Residual deviance: 0.012672 on 7 degrees of freedom`	7636	`Residual deviance: 0.012672 on 7 degrees of freedom`
Line 7756...		Line 7756...
7756	`learning , . . 1`	7756	`learning , . . 1`
7757	`raises . , . , 1`	7757	`raises . , . , 1`
7758	`critical . 1`	7758	`critical . 1`
7759	`advance . . . 1`	7759	`advance . . . 1`
7760	`attr(,"legend")`	7760	`attr(,"legend")`
7761	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	7761	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
7762	`> heatmap(Ca, symm = TRUE, margins = c(6,6)) # with reorder()`	7762	`> heatmap(Ca, symm = TRUE, margins = c(6,6)) # with reorder()`
7763	`> heatmap(Ca, Rowv = FALSE, symm = TRUE, margins = c(6,6)) # _NO_ reorder()`	7763	`> heatmap(Ca, Rowv = FALSE, symm = TRUE, margins = c(6,6)) # _NO_ reorder()`
7764	`> ## slightly artificial with color bar, without and with ordering:`	7764	`> ## slightly artificial with color bar, without and with ordering:`
7765	`> cc <- rainbow(nrow(Ca))`	7765	`> cc <- rainbow(nrow(Ca))`
7766	`> heatmap(Ca, Rowv = FALSE, symm = TRUE, RowSideColors = cc, ColSideColors = cc,`	7766	`> heatmap(Ca, Rowv = FALSE, symm = TRUE, RowSideColors = cc, ColSideColors = cc,`
Line 7782...		Line 7782...
7782	`ORAL * * B B * B B 1`	7782	`ORAL * * B B * B B 1`
7783	`WRIT * + B * * B B B 1`	7783	`WRIT * + B * * B B B 1`
7784	`PHYS , , + + + + + + + 1`	7784	`PHYS , , + + + + + + + 1`
7785	`RTEN * * * * * B * B B * 1`	7785	`RTEN * * * * * B * B B * 1`
7786	`attr(,"legend")`	7786	`attr(,"legend")`
7787	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	7787	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
7788	`>`	7788	`>`
7789	`> hU <- heatmap(cU, Rowv = FALSE, symm = TRUE, col = topo.colors(16),`	7789	`> hU <- heatmap(cU, Rowv = FALSE, symm = TRUE, col = topo.colors(16),`
7790	`+ distfun = function(c) as.dist(1 - c), keep.dendro = TRUE)`	7790	`+ distfun = function(c) as.dist(1 - c), keep.dendro = TRUE)`
7791	`> ## The Correlation matrix with same reordering:`	7791	`> ## The Correlation matrix with same reordering:`
7792	`> round(100 * cU[hU[[1]], hU[[2]]])`	7792	`> round(100 * cU[hU[[1]], hU[[2]]])`
Line 7909...		Line 7909...
7909	`> integrate(integrand, lower = 0, upper = 10)`	7909	`> integrate(integrand, lower = 0, upper = 10)`
7910	`2.529038 with absolute error < 3e-04`	7910	`2.529038 with absolute error < 3e-04`
7911	`> integrate(integrand, lower = 0, upper = 100000)`	7911	`> integrate(integrand, lower = 0, upper = 100000)`
7912	`3.135268 with absolute error < 4.2e-07`	7912	`3.135268 with absolute error < 4.2e-07`
7913	`> integrate(integrand, lower = 0, upper = 1000000, stop.on.error = FALSE)`	7913	`> integrate(integrand, lower = 0, upper = 1000000, stop.on.error = FALSE)`
7914	`failed with message 'the integral is probably divergent'`	7914	`failed with message ‘the integral is probably divergent’`
7915	`>`	7915	`>`
7916	`> ## some functions do not handle vector input properly`	7916	`> ## some functions do not handle vector input properly`
7917	`> f <- function(x) 2.0`	7917	`> f <- function(x) 2.0`
7918	`> try(integrate(f, 0, 1))`	7918	`> try(integrate(f, 0, 1))`
7919	`Error in integrate(f, 0, 1) :`	7919	`Error in integrate(f, 0, 1) :`
Line 8585...		Line 8585...
8585	`pop15 -0.4611931 0.1446422 -3.189 0.002603 **`	8585	`pop15 -0.4611931 0.1446422 -3.189 0.002603 **`
8586	`pop75 -1.6914977 1.0835989 -1.561 0.125530`	8586	`pop75 -1.6914977 1.0835989 -1.561 0.125530`
8587	`dpi -0.0003369 0.0009311 -0.362 0.719173`	8587	`dpi -0.0003369 0.0009311 -0.362 0.719173`
8588	`ddpi 0.4096949 0.1961971 2.088 0.042471 *`	8588	`ddpi 0.4096949 0.1961971 2.088 0.042471 *`
8589	`---`	8589	`---`
8590	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	8590	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
8591		8591
8592	`Residual standard error: 3.803 on 45 degrees of freedom`	8592	`Residual standard error: 3.803 on 45 degrees of freedom`
8593	`Multiple R-squared: 0.3385, Adjusted R-squared: 0.2797`	8593	`Multiple R-squared: 0.3385, Adjusted R-squared: 0.2797`
8594	`F-statistic: 5.756 on 4 and 45 DF, p-value: 0.0007904`	8594	`F-statistic: 5.756 on 4 and 45 DF, p-value: 0.0007904`
8595		8595
Line 9117...		Line 9117...
9117	`N:P 1 0.30158 2.3750 2 11 0.13888`	9117	`N:P 1 0.30158 2.3750 2 11 0.13888`
9118	`N:K 1 0.21654 1.5201 2 11 0.26127`	9118	`N:K 1 0.21654 1.5201 2 11 0.26127`
9119	`P:K 1 0.41992 3.9814 2 11 0.05003 .`	9119	`P:K 1 0.41992 3.9814 2 11 0.05003 .`
9120	`Residuals 12`	9120	`Residuals 12`
9121	`---`	9121	`---`
9122	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	9122	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
9123	`>`	9123	`>`
9124	`> ( npk2.aovE <- manova(cbind(yield, foo) ~ NPK + Error(block), npk2) )`	9124	`> ( npk2.aovE <- manova(cbind(yield, foo) ~ NPK + Error(block), npk2) )`
9125		9125
9126	`Call:`	9126	`Call:`
9127	`manova(cbind(yield, foo) ~ N * P * K + Error(block), npk2)`	9127	`manova(cbind(yield, foo) ~ N * P * K + Error(block), npk2)`
Line 9170...		Line 9170...
9170	`N:P 1 0.30158 2.3750 2 11 0.13888`	9170	`N:P 1 0.30158 2.3750 2 11 0.13888`
9171	`N:K 1 0.21654 1.5201 2 11 0.26127`	9171	`N:K 1 0.21654 1.5201 2 11 0.26127`
9172	`P:K 1 0.41992 3.9814 2 11 0.05003 .`	9172	`P:K 1 0.41992 3.9814 2 11 0.05003 .`
9173	`Residuals 12`	9173	`Residuals 12`
9174	`---`	9174	`---`
9175	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	9175	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
9176	`>`	9176	`>`
9177	`>`	9177	`>`
9178	`>`	9178	`>`
9179	`>`	9179	`>`
9180	`>`	9180	`>`
Line 10264...		Line 10264...
10264	`Estimate Std. Error t value Pr(>\|t\|)`	10264	`Estimate Std. Error t value Pr(>\|t\|)`
10265	`Asym 2.3452 0.0782 30.0 2.2e-13 ***`	10265	`Asym 2.3452 0.0782 30.0 2.2e-13 ***`
10266	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`	10266	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`
10267	`scal 1.0415 0.0323 32.3 8.5e-14 ***`	10267	`scal 1.0415 0.0323 32.3 8.5e-14 ***`
10268	`---`	10268	`---`
10269	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10269	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10270		10270
10271	`Residual standard error: 0.0192 on 13 degrees of freedom`	10271	`Residual standard error: 0.0192 on 13 degrees of freedom`
10272		10272
10273	`> ## the coefficients only:`	10273	`> ## the coefficients only:`
10274	`> coef(fm1DNase1)`	10274	`> coef(fm1DNase1)`
Line 10294...		Line 10294...
10294	`Estimate Std. Error t value Pr(>\|t\|)`	10294	`Estimate Std. Error t value Pr(>\|t\|)`
10295	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`	10295	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`
10296	`scal 1.0415 0.0323 32.3 8.5e-14 ***`	10296	`scal 1.0415 0.0323 32.3 8.5e-14 ***`
10297	`.lin 2.3452 0.0782 30.0 2.2e-13 ***`	10297	`.lin 2.3452 0.0782 30.0 2.2e-13 ***`
10298	`---`	10298	`---`
10299	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10299	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10300		10300
10301	`Residual standard error: 0.0192 on 13 degrees of freedom`	10301	`Residual standard error: 0.0192 on 13 degrees of freedom`
10302		10302
10303	`>`	10303	`>`
10304	`> ## without conditional linearity`	10304	`> ## without conditional linearity`
Line 10313...		Line 10313...
10313	`Estimate Std. Error t value Pr(>\|t\|)`	10313	`Estimate Std. Error t value Pr(>\|t\|)`
10314	`Asym 2.3452 0.0782 30.0 2.2e-13 ***`	10314	`Asym 2.3452 0.0782 30.0 2.2e-13 ***`
10315	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`	10315	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`
10316	`scal 1.0415 0.0323 32.3 8.5e-14 ***`	10316	`scal 1.0415 0.0323 32.3 8.5e-14 ***`
10317	`---`	10317	`---`
10318	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10318	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10319		10319
10320	`Residual standard error: 0.0192 on 13 degrees of freedom`	10320	`Residual standard error: 0.0192 on 13 degrees of freedom`
10321		10321
10322	`>`	10322	`>`
10323	`> ## using Port's nl2sol algorithm`	10323	`> ## using Port's nl2sol algorithm`
Line 10333...		Line 10333...
10333	`Estimate Std. Error t value Pr(>\|t\|)`	10333	`Estimate Std. Error t value Pr(>\|t\|)`
10334	`Asym 2.3452 0.0782 30.0 2.2e-13 ***`	10334	`Asym 2.3452 0.0782 30.0 2.2e-13 ***`
10335	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`	10335	`xmid 1.4831 0.0814 18.2 1.2e-10 ***`
10336	`scal 1.0415 0.0323 32.3 8.5e-14 ***`	10336	`scal 1.0415 0.0323 32.3 8.5e-14 ***`
10337	`---`	10337	`---`
10338	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10338	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10339		10339
10340	`Residual standard error: 0.0192 on 13 degrees of freedom`	10340	`Residual standard error: 0.0192 on 13 degrees of freedom`
10341		10341
10342	`Algorithm "port", convergence message: relative convergence (4)`	10342	`Algorithm "port", convergence message: relative convergence (4)`
10343		10343
Line 10366...		Line 10366...
10366	`Parameters:`	10366	`Parameters:`
10367	`Estimate Std. Error t value Pr(>\|t\|)`	10367	`Estimate Std. Error t value Pr(>\|t\|)`
10368	`Vm 2.07e+02 9.22e+00 22.42 7.0e-10 ***`	10368	`Vm 2.07e+02 9.22e+00 22.42 7.0e-10 ***`
10369	`K 5.46e-02 7.98e-03 6.84 4.5e-05 ***`	10369	`K 5.46e-02 7.98e-03 6.84 4.5e-05 ***`
10370	`---`	10370	`---`
10371	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10371	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10372		10372
10373	`Residual standard error: 1.21 on 10 degrees of freedom`	10373	`Residual standard error: 1.21 on 10 degrees of freedom`
10374		10374
10375	`>`	10375	`>`
10376	`> ## Passing arguments using a list that can not be coerced to a data.frame`	10376	`> ## Passing arguments using a list that can not be coerced to a data.frame`
Line 10443...		Line 10443...
10443	`> x <- -(1:100)/10`	10443	`> x <- -(1:100)/10`
10444	`> y <- 100 + 10 * exp(x / 2) + rnorm(x)/10`	10444	`> y <- 100 + 10 * exp(x / 2) + rnorm(x)/10`
10445	`> nlmod <- nls(y ~ Const + A * exp(B * x))`	10445	`> nlmod <- nls(y ~ Const + A * exp(B * x))`
10446	`Warning in nls(y ~ Const + A * exp(B * x)) :`	10446	`Warning in nls(y ~ Const + A * exp(B * x)) :`
10447	`No starting values specified for some parameters.`	10447	`No starting values specified for some parameters.`
10448	`Initializing 'Const', 'A', 'B' to '1.'.`	10448	`Initializing ‘Const’, ‘A’, ‘B’ to '1.'.`
10449	`Consider specifying 'start' or using a selfStart model`	10449	`Consider specifying 'start' or using a selfStart model`
10450	`>`	10450	`>`
10451	`> plot(x,y, main = "nls(*), data, true function and fit, n=100")`	10451	`> plot(x,y, main = "nls(*), data, true function and fit, n=100")`
10452	`> curve(100 + 10 * exp(x / 2), col = 4, add = TRUE)`	10452	`> curve(100 + 10 * exp(x / 2), col = 4, add = TRUE)`
10453	`> lines(x, predict(nlmod), col = 2)`	10453	`> lines(x, predict(nlmod), col = 2)`
Line 10483...		Line 10483...
10483	`Estimate Std. Error t value Pr(>\|t\|)`	10483	`Estimate Std. Error t value Pr(>\|t\|)`
10484	`th 0.608 0.115 5.31 1.9e-06 ***`	10484	`th 0.608 0.115 5.31 1.9e-06 ***`
10485	`.lin1 28.963 1.230 23.55 < 2e-16 ***`	10485	`.lin1 28.963 1.230 23.55 < 2e-16 ***`
10486	`.lin2 -34.227 3.793 -9.02 1.4e-12 ***`	10486	`.lin2 -34.227 3.793 -9.02 1.4e-12 ***`
10487	`---`	10487	`---`
10488	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10488	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10489		10489
10490	`Residual standard error: 4.67 on 57 degrees of freedom`	10490	`Residual standard error: 4.67 on 57 degrees of freedom`
10491		10491
10492	`>`	10492	`>`
10493	`> ## Then we use nls' indexing feature for parameters in non-linear`	10493	`> ## Then we use nls' indexing feature for parameters in non-linear`
Line 10547...		Line 10547...
10547	`b19 -28.969 7.235 -4.00 0.00092 ***`	10547	`b19 -28.969 7.235 -4.00 0.00092 ***`
10548	`b20 -36.917 8.033 -4.60 0.00026 ***`	10548	`b20 -36.917 8.033 -4.60 0.00026 ***`
10549	`b21 -26.508 7.012 -3.78 0.00149 **`	10549	`b21 -26.508 7.012 -3.78 0.00149 **`
10550	`th 0.797 0.127 6.30 8.0e-06 ***`	10550	`th 0.797 0.127 6.30 8.0e-06 ***`
10551	`---`	10551	`---`
10552	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10552	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10553		10553
10554	`Residual standard error: 1.11 on 17 degrees of freedom`	10554	`Residual standard error: 1.11 on 17 degrees of freedom`
10555		10555
10556	`> ## Don't show:`	10556	`> ## Don't show:`
10557	`> options(od)`	10557	`> options(od)`
Line 10691...		Line 10691...
10691	`Response: extra`	10691	`Response: extra`
10692	`Df Sum Sq Mean Sq F value Pr(>F)`	10692	`Df Sum Sq Mean Sq F value Pr(>F)`
10693	`group 1 12.482 12.4820 3.4626 0.07919 .`	10693	`group 1 12.482 12.4820 3.4626 0.07919 .`
10694	`Residuals 18 64.886 3.6048`	10694	`Residuals 18 64.886 3.6048`
10695	`---`	10695	`---`
10696	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	10696	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
10697	`>`	10697	`>`
10698	`>`	10698	`>`
10699	`>`	10699	`>`
10700	`> cleanEx()`	10700	`> cleanEx()`
10701	`> nameEx("optim")`	10701	`> nameEx("optim")`
Line 11746...		Line 11746...
11746	`[1] "link-glm"`	11746	`[1] "link-glm"`
11747	`> quasi(link = power(1/3))[c("linkfun", "linkinv")]`	11747	`> quasi(link = power(1/3))[c("linkfun", "linkinv")]`
11748	`$linkfun`	11748	`$linkfun`
11749	`function (mu)`	11749	`function (mu)`
11750	`mu^lambda`	11750	`mu^lambda`
11751	`<bytecode: 0x7f93488e2630>`	11751	`<bytecode: 0x8b86170>`
11752	`<environment: 0x7f9348866548>`	11752	`<environment: 0x8b7b8e8>`
11753		11753
11754	`$linkinv`	11754	`$linkinv`
11755	`function (eta)`	11755	`function (eta)`
11756	`pmax(eta^(1/lambda), .Machine$double.eps)`	11756	`pmax(eta^(1/lambda), .Machine$double.eps)`
11757	`<bytecode: 0x7f93488e2748>`	11757	`<bytecode: 0x8b86288>`
11758	`<environment: 0x7f9348866548>`	11758	`<environment: 0x8b7b8e8>`
11759		11759
11760	`>`	11760	`>`
11761	`>`	11761	`>`
11762	`>`	11762	`>`
11763	`> cleanEx()`	11763	`> cleanEx()`
Line 12338...		Line 12338...
12338	`(Intercept) -2.9935 0.5527 -5.416 6.09e-08 ***`	12338	`(Intercept) -2.9935 0.5527 -5.416 6.09e-08 ***`
12339	`sexM 0.1750 0.7783 0.225 0.822`	12339	`sexM 0.1750 0.7783 0.225 0.822`
12340	`ldose 0.9060 0.1671 5.422 5.89e-08 ***`	12340	`ldose 0.9060 0.1671 5.422 5.89e-08 ***`
12341	`sexM:ldose 0.3529 0.2700 1.307 0.191`	12341	`sexM:ldose 0.3529 0.2700 1.307 0.191`
12342	`---`	12342	`---`
12343	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	12343	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
12344		12344
12345	`(Dispersion parameter for binomial family taken to be 1)`	12345	`(Dispersion parameter for binomial family taken to be 1)`
12346		12346
12347	`Null deviance: 124.8756 on 11 degrees of freedom`	12347	`Null deviance: 124.8756 on 11 degrees of freedom`
12348	`Residual deviance: 4.9937 on 8 degrees of freedom`	12348	`Residual deviance: 4.9937 on 8 degrees of freedom`
Line 13074...		Line 13074...
13074	`Estimate Std.Err Z value Pr(>z)`	13074	`Estimate Std.Err Z value Pr(>z)`
13075	`[1,] 9.3735 4.4447 2.1089 0.0349492 *`	13075	`[1,] 9.3735 4.4447 2.1089 0.0349492 *`
13076	`[2,] 10.1836 3.5496 2.8689 0.0041185 **`	13076	`[2,] 10.1836 3.5496 2.8689 0.0041185 **`
13077	`[3,] 9.1644 2.7365 3.3490 0.0008111 ***`	13077	`[3,] 9.1644 2.7365 3.3490 0.0008111 ***`
13078	`---`	13078	`---`
13079	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	13079	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
13080	`> op <- options(show.coef.Pvalues = FALSE)`	13080	`> op <- options(show.coef.Pvalues = FALSE)`
13081	`> printCoefmat(cmat, digits = 2)`	13081	`> printCoefmat(cmat, digits = 2)`
13082	`Estimate Std.Err Z value`	13082	`Estimate Std.Err Z value`
13083	`[1,] 9.4 4.4 2.1`	13083	`[1,] 9.4 4.4 2.1`
13084	`[2,] 10.2 3.5 2.9`	13084	`[2,] 10.2 3.5 2.9`
Line 13087...		Line 13087...
13087	`Estimate Std.Err Z value Pr(>z)`	13087	`Estimate Std.Err Z value Pr(>z)`
13088	`[1,] 9.4 4.4 2.1 0.035 *`	13088	`[1,] 9.4 4.4 2.1 0.035 *`
13089	`[2,] 10.2 3.5 2.9 0.004 **`	13089	`[2,] 10.2 3.5 2.9 0.004 **`
13090	`[3,] 9.2 2.7 3.3 8e-04 ***`	13090	`[3,] 9.2 2.7 3.3 8e-04 ***`
13091	`---`	13091	`---`
13092	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	13092	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
13093	`> options(op) # restore`	13093	`> options(op) # restore`
13094	`>`	13094	`>`
13095	`>`	13095	`>`
13096	`>`	13096	`>`
13097	`> cleanEx()`	13097	`> cleanEx()`
Line 13901...		Line 13901...
13901	`(Intercept) 29.278 3.162 9.260 2e-12 ***`	13901	`(Intercept) 29.278 3.162 9.260 2e-12 ***`
13902	`woolB -5.778 3.162 -1.827 0.0736 .`	13902	`woolB -5.778 3.162 -1.827 0.0736 .`
13903	`tensionL 10.000 3.872 2.582 0.0128 *`	13903	`tensionL 10.000 3.872 2.582 0.0128 *`
13904	`tensionH -4.722 3.872 -1.219 0.2284`	13904	`tensionH -4.722 3.872 -1.219 0.2284`
13905	`---`	13905	`---`
13906	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	13906	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
13907		13907
13908	`Residual standard error: 11.62 on 50 degrees of freedom`	13908	`Residual standard error: 11.62 on 50 degrees of freedom`
13909	`Multiple R-squared: 0.2691, Adjusted R-squared: 0.2253`	13909	`Multiple R-squared: 0.2691, Adjusted R-squared: 0.2253`
13910	`F-statistic: 6.138 on 3 and 50 DF, p-value: 0.00123`	13910	`F-statistic: 6.138 on 3 and 50 DF, p-value: 0.00123`
13911		13911
Line 14676...		Line 14676...
14676	`A:B 2 81.56 40.78 4.823 0.01527 *`	14676	`A:B 2 81.56 40.78 4.823 0.01527 *`
14677	`A:B: C1 1 13.50 13.50 1.597 0.21612`	14677	`A:B: C1 1 13.50 13.50 1.597 0.21612`
14678	`A:B: C2 1 68.06 68.06 8.049 0.00809 **`	14678	`A:B: C2 1 68.06 68.06 8.049 0.00809 **`
14679	`Residuals 30 253.67 8.46`	14679	`Residuals 30 253.67 8.46`
14680	`---`	14680	`---`
14681	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	14681	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
14682	`> ## t.stat^2 is the F value on the A:B: C1 line (with Helmert contrasts)`	14682	`> ## t.stat^2 is the F value on the A:B: C1 line (with Helmert contrasts)`
14683	`> ## Now look at all three interaction contrasts`	14683	`> ## Now look at all three interaction contrasts`
14684	`> cont <- c(1, -1)[A] * cbind(c(1, -1, 0), c(1, 0, -1), c(0, 1, -1))[B,]`	14684	`> cont <- c(1, -1)[A] * cbind(c(1, -1, 0), c(1, 0, -1), c(0, 1, -1))[B,]`
14685	`> se.contrast(fit, cont) # same, due to balance.`	14685	`> se.contrast(fit, cont) # same, due to balance.`
14686	`Contrast 1 Contrast 2 Contrast 3`	14686	`Contrast 1 Contrast 2 Contrast 3`
Line 14718...		Line 14718...
14718	`eff.vl> (fit <- aov(Yield ~ ABC + Error(Block), data = aovdat))`	14718	`eff.vl> (fit <- aov(Yield ~ ABC + Error(Block), data = aovdat))`
14719		14719
14720	`Call:`	14720	`Call:`
14721	`aov(formula = Yield ~ A * B * C + Error(Block), data = aovdat)`	14721	`aov(formula = Yield ~ A * B * C + Error(Block), data = aovdat)`
14722		14722
14723	`Grand Mean: 291.5937`	14723	`Grand Mean: 291.5938`
14724		14724
14725	`Stratum 1: Block`	14725	`Stratum 1: Block`
14726		14726
14727	`Terms:`	14727	`Terms:`
14728	`A:B A:C B:C A:B:C Residuals`	14728	`A:B A:C B:C A:B:C Residuals`
Line 14737...		Line 14737...
14737	`Terms:`	14737	`Terms:`
14738	`A B C A:B A:C B:C`	14738	`A B C A:B A:C B:C`
14739	`Sum of Squares 3465.28 161170.03 278817.78 28.17 1802.67 11528.17`	14739	`Sum of Squares 3465.28 161170.03 278817.78 28.17 1802.67 11528.17`
14740	`Deg. of Freedom 1 1 1 1 1 1`	14740	`Deg. of Freedom 1 1 1 1 1 1`
14741	`A:B:C Residuals`	14741	`A:B:C Residuals`
14742	`Sum of Squares 45.38 5423.28`	14742	`Sum of Squares 45.37 5423.28`
14743	`Deg. of Freedom 1 17`	14743	`Deg. of Freedom 1 17`
14744		14744
14745	`Residual standard error: 17.86103`	14745	`Residual standard error: 17.86103`
14746	`Estimated effects are balanced`	14746	`Estimated effects are balanced`
14747		14747
Line 15547...		Line 15547...
15547	`>`	15547	`>`
15548	`> ## look at the internal structure:`	15548	`> ## look at the internal structure:`
15549	`> unclass(sfun0)`	15549	`> unclass(sfun0)`
15550	`function (v)`	15550	`function (v)`
15551	`.approxfun(x, y, v, method, yleft, yright, f)`	15551	`.approxfun(x, y, v, method, yleft, yright, f)`
15552	`<bytecode: 0x7f9344070e30>`	15552	`<bytecode: 0x4a01dc0>`
15553	`<environment: 0x7f9349fb2dc8>`	15553	`<environment: 0xa664e58>`
15554	`attr(,"call")`	15554	`attr(,"call")`
15555	`stepfun(1:3, y0, f = 0)`	15555	`stepfun(1:3, y0, f = 0)`
15556	`> ls(envir = environment(sfun0))`	15556	`> ls(envir = environment(sfun0))`
15557	`[1] "f" "method" "x" "y" "yleft" "yright"`	15557	`[1] "f" "method" "x" "y" "yleft" "yright"`
15558	`>`	15558	`>`
Line 15785...		Line 15785...
15785	`Coefficients:`	15785	`Coefficients:`
15786	`Estimate Std. Error t value Pr(>\|t\|)`	15786	`Estimate Std. Error t value Pr(>\|t\|)`
15787	`groupCtl 5.0320 0.2202 22.85 9.55e-15 ***`	15787	`groupCtl 5.0320 0.2202 22.85 9.55e-15 ***`
15788	`groupTrt 4.6610 0.2202 21.16 3.62e-14 ***`	15788	`groupTrt 4.6610 0.2202 21.16 3.62e-14 ***`
15789	`---`	15789	`---`
15790	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	15790	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
15791		15791
15792	`Residual standard error: 0.6964 on 18 degrees of freedom`	15792	`Residual standard error: 0.6964 on 18 degrees of freedom`
15793	`Multiple R-squared: 0.9818, Adjusted R-squared: 0.9798`	15793	`Multiple R-squared: 0.9818, Adjusted R-squared: 0.9798`
15794	`F-statistic: 485.1 on 2 and 18 DF, p-value: < 2.2e-16`	15794	`F-statistic: 485.1 on 2 and 18 DF, p-value: < 2.2e-16`
15795		15795
Line 15814...		Line 15814...
15814	`Estimate Std. Error t value Pr(>\|t\|)`	15814	`Estimate Std. Error t value Pr(>\|t\|)`
15815	`(Intercept) 5.0320 0.2202 22.850 9.55e-15 ***`	15815	`(Intercept) 5.0320 0.2202 22.850 9.55e-15 ***`
15816	`groupTrt -0.3710 0.3114 -1.191 0.249`	15816	`groupTrt -0.3710 0.3114 -1.191 0.249`
15817	`I(group != "Ctl")TRUE NA NA NA NA`	15817	`I(group != "Ctl")TRUE NA NA NA NA`
15818	`---`	15818	`---`
15819	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	15819	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
15820		15820
15821	`Residual standard error: 0.6964 on 18 degrees of freedom`	15821	`Residual standard error: 0.6964 on 18 degrees of freedom`
15822	`Multiple R-squared: 0.07308, Adjusted R-squared: 0.02158`	15822	`Multiple R-squared: 0.07308, Adjusted R-squared: 0.02158`
15823	`F-statistic: 1.419 on 1 and 18 DF, p-value: 0.249`	15823	`F-statistic: 1.419 on 1 and 18 DF, p-value: 0.249`
15824		15824
Line 15916...		Line 15916...
15916	`> ii <- setNames(0:8, 0:8)`	15916	`> ii <- setNames(0:8, 0:8)`
15917	`> symnum(ii, cut = 2*(0:4), sym = c(".", "-", "+", "$"))`	15917	`> symnum(ii, cut = 2*(0:4), sym = c(".", "-", "+", "$"))`
15918	`0 1 2 3 4 5 6 7 8`	15918	`0 1 2 3 4 5 6 7 8`
15919	`. . . - - + + $ $`	15919	`. . . - - + + $ $`
15920	`attr(,"legend")`	15920	`attr(,"legend")`
15921	`[1] 0 '.' 2 '-' 4 '+' 6 '$' 8`	15921	`[1] 0 ‘.’ 2 ‘-’ 4 ‘+’ 6 ‘$’ 8`
15922	`> symnum(ii, cut = 2*(0:4), sym = c(".", "-", "+", "$"), show.max = TRUE)`	15922	`> symnum(ii, cut = 2*(0:4), sym = c(".", "-", "+", "$"), show.max = TRUE)`
15923	`0 1 2 3 4 5 6 7 8`	15923	`0 1 2 3 4 5 6 7 8`
15924	`. . . - - + + $ 8`	15924	`. . . - - + + $ 8`
15925	`attr(,"legend")`	15925	`attr(,"legend")`
15926	`[1] 0 '.' 2 '-' 4 '+' 6 '$' 8`	15926	`[1] 0 ‘.’ 2 ‘-’ 4 ‘+’ 6 ‘$’ 8`
15927	`>`	15927	`>`
15928	`> symnum(1:12 %% 3 == 0) # --> "\|" = TRUE, "." = FALSE for logical`	15928	`> symnum(1:12 %% 3 == 0) # --> "\|" = TRUE, "." = FALSE for logical`
15929	`[1] . . \| . . \| . . \| . . \|`	15929	`[1] . . \| . . \| . . \| . . \|`
15930	`>`	15930	`>`
15931	`> ## Pascal's Triangle modulo 2 -- odd and even numbers:`	15931	`> ## Pascal's Triangle modulo 2 -- odd and even numbers:`
Line 15983...		Line 15983...
15983	`learning , . .`	15983	`learning , . .`
15984	`raises . , . ,`	15984	`raises . , . ,`
15985	`critical .`	15985	`critical .`
15986	`advance . . .`	15986	`advance . . .`
15987	`attr(,"legend")`	15987	`attr(,"legend")`
15988	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	15988	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
15989	`> symnum(cor(attitude), abbr. = NULL)`	15989	`> symnum(cor(attitude), abbr. = NULL)`
15990		15990
15991	`rating 1`	15991	`rating 1`
15992	`complaints + 1`	15992	`complaints + 1`
15993	`privileges . . 1`	15993	`privileges . . 1`
15994	`learning , . . 1`	15994	`learning , . . 1`
15995	`raises . , . , 1`	15995	`raises . , . , 1`
15996	`critical . 1`	15996	`critical . 1`
15997	`advance . . . 1`	15997	`advance . . . 1`
15998	`attr(,"legend")`	15998	`attr(,"legend")`
15999	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	15999	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16000	`> symnum(cor(attitude), abbr. = FALSE)`	16000	`> symnum(cor(attitude), abbr. = FALSE)`
16001	`rating complaints privileges learning raises critical advance`	16001	`rating complaints privileges learning raises critical advance`
16002	`rating 1`	16002	`rating 1`
16003	`complaints + 1`	16003	`complaints + 1`
16004	`privileges . . 1`	16004	`privileges . . 1`
16005	`learning , . . 1`	16005	`learning , . . 1`
16006	`raises . , . , 1`	16006	`raises . , . , 1`
16007	`critical . 1`	16007	`critical . 1`
16008	`advance . . . 1`	16008	`advance . . . 1`
16009	`attr(,"legend")`	16009	`attr(,"legend")`
16010	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16010	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16011	`> symnum(cor(attitude), abbr. = 2)`	16011	`> symnum(cor(attitude), abbr. = 2)`
16012	`rt cm pr lr rs cr ad`	16012	`rt cm pr lr rs cr ad`
16013	`rating 1`	16013	`rating 1`
16014	`complaints + 1`	16014	`complaints + 1`
16015	`privileges . . 1`	16015	`privileges . . 1`
16016	`learning , . . 1`	16016	`learning , . . 1`
16017	`raises . , . , 1`	16017	`raises . , . , 1`
16018	`critical . 1`	16018	`critical . 1`
16019	`advance . . . 1`	16019	`advance . . . 1`
16020	`attr(,"legend")`	16020	`attr(,"legend")`
16021	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16021	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16022	`>`	16022	`>`
16023	`> symnum(cor(rbind(1, rnorm(25), rnorm(25)^2)))`	16023	`> symnum(cor(rbind(1, rnorm(25), rnorm(25)^2)))`
16024		16024
16025	`[1,] 1`	16025	`[1,] 1`
16026	`[2,] + 1`	16026	`[2,] + 1`
Line 16046...		Line 16046...
16046	`[22,] . , , , + . B B B , + + . . + , , B B + B 1`	16046	`[22,] . , , , + . B B B , + + . . + , , B B + B 1`
16047	`[23,] B , , . , , . . , . , B + + + , 1`	16047	`[23,] B , , . , , . . , . , B + + + , 1`
16048	`[24,] * , , . , , . , . . * * . , , . B 1`	16048	`[24,] * , , . , , . , . . * * . , , . B 1`
16049	`[25,] B + . . + . , . . . , B , * * . + . B B 1`	16049	`[25,] B + . . + . , . . . , B , * * . + . B B 1`
16050	`attr(,"legend")`	16050	`attr(,"legend")`
16051	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16051	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16052	`> symnum(cor(matrix(rexp(30, 1), 5, 18))) # <<-- PATTERN ! --`	16052	`> symnum(cor(matrix(rexp(30, 1), 5, 18))) # <<-- PATTERN ! --`
16053		16053
16054	`[1,] 1`	16054	`[1,] 1`
16055	`[2,] . 1`	16055	`[2,] . 1`
16056	`[3,] 1`	16056	`[3,] 1`
Line 16068...		Line 16068...
16068	`[15,] 1 . 1 . 1`	16068	`[15,] 1 . 1 . 1`
16069	`[16,] . . 1 . . 1 . . 1`	16069	`[16,] . . 1 . . 1 . . 1`
16070	`[17,] , . 1 , , . 1 , , . 1`	16070	`[17,] , . 1 , , . 1 , , . 1`
16071	`[18,] , , 1 , , 1 , , 1`	16071	`[18,] , , 1 , , 1 , , 1`
16072	`attr(,"legend")`	16072	`attr(,"legend")`
16073	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16073	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16074	`> symnum(cm1 <- cor(matrix(rnorm(90) , 5, 18))) # < White Noise SMALL n`	16074	`> symnum(cm1 <- cor(matrix(rnorm(90) , 5, 18))) # < White Noise SMALL n`
16075		16075
16076	`[1,] 1`	16076	`[1,] 1`
16077	`[2,] . 1`	16077	`[2,] . 1`
16078	`[3,] . . 1`	16078	`[3,] . . 1`
Line 16090...		Line 16090...
16090	`[15,] . . . . . . + 1`	16090	`[15,] . . . . . . + 1`
16091	`[16,] . , . . . . . . 1`	16091	`[16,] . , . . . . . . 1`
16092	`[17,] , + , + . . * . . 1`	16092	`[17,] , + , + . . * . . 1`
16093	`[18,] . . * , . . . , , . . 1`	16093	`[18,] . . * , . . . , , . . 1`
16094	`attr(,"legend")`	16094	`attr(,"legend")`
16095	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16095	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16096	`> symnum(cm1, diag = FALSE)`	16096	`> symnum(cm1, diag = FALSE)`
16097		16097
16098	`[1,]`	16098	`[1,]`
16099	`[2,] .`	16099	`[2,] .`
16100	`[3,] . .`	16100	`[3,] . .`
Line 16112...		Line 16112...
16112	`[15,] . . . . . . +`	16112	`[15,] . . . . . . +`
16113	`[16,] . , . . . . . .`	16113	`[16,] . , . . . . . .`
16114	`[17,] , + , + . . * . .`	16114	`[17,] , + , + . . * . .`
16115	`[18,] . . * , . . . , , . .`	16115	`[18,] . . * , . . . , , . .`
16116	`attr(,"legend")`	16116	`attr(,"legend")`
16117	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16117	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16118	`> symnum(cm2 <- cor(matrix(rnorm(900), 50, 18))) # < White Noise "BIG" n`	16118	`> symnum(cm2 <- cor(matrix(rnorm(900), 50, 18))) # < White Noise "BIG" n`
16119		16119
16120	`[1,] 1`	16120	`[1,] 1`
16121	`[2,] 1`	16121	`[2,] 1`
16122	`[3,] 1`	16122	`[3,] 1`
Line 16134...		Line 16134...
16134	`[15,] 1`	16134	`[15,] 1`
16135	`[16,] 1`	16135	`[16,] 1`
16136	`[17,] 1`	16136	`[17,] 1`
16137	`[18,] 1`	16137	`[18,] 1`
16138	`attr(,"legend")`	16138	`attr(,"legend")`
16139	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16139	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16140	`> symnum(cm2, lower = FALSE)`	16140	`> symnum(cm2, lower = FALSE)`
16141		16141
16142	`[1,] 1`	16142	`[1,] 1`
16143	`[2,] 1`	16143	`[2,] 1`
16144	`[3,] 1`	16144	`[3,] 1`
Line 16156...		Line 16156...
16156	`[15,] 1`	16156	`[15,] 1`
16157	`[16,] 1`	16157	`[16,] 1`
16158	`[17,] 1`	16158	`[17,] 1`
16159	`[18,] 1`	16159	`[18,] 1`
16160	`attr(,"legend")`	16160	`attr(,"legend")`
16161	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1`	16161	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1`
16162	`>`	16162	`>`
16163	`> ## NA's:`	16163	`> ## NA's:`
16164	`> Cm <- cor(matrix(rnorm(60), 10, 6)); Cm[c(3,6), 2] <- NA`	16164	`> Cm <- cor(matrix(rnorm(60), 10, 6)); Cm[c(3,6), 2] <- NA`
16165	`> symnum(Cm, show.max = NULL)`	16165	`> symnum(Cm, show.max = NULL)`
16166		16166
Line 16169...		Line 16169...
16169	`[3,] . ?`	16169	`[3,] . ?`
16170	`[4,] . ,`	16170	`[4,] . ,`
16171	`[5,] .`	16171	`[5,] .`
16172	`[6,] , ?`	16172	`[6,] , ?`
16173	`attr(,"legend")`	16173	`attr(,"legend")`
16174	`[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1 \t ## NA: '?'`	16174	`[1] 0 ‘ ’ 0.3 ‘.’ 0.6 ‘,’ 0.8 ‘+’ 0.9 ‘*’ 0.95 ‘B’ 1 \t ## NA: ‘?’`
16175	`>`	16175	`>`
16176	`> ## Graphical P-values (aka "significance stars"):`	16176	`> ## Graphical P-values (aka "significance stars"):`
16177	`> pval <- rev(sort(c(outer(1:6, 10^-(1:3)))))`	16177	`> pval <- rev(sort(c(outer(1:6, 10^-(1:3)))))`
16178	`> symp <- symnum(pval, corr = FALSE,`	16178	`> symp <- symnum(pval, corr = FALSE,`
16179	`+ cutpoints = c(0, .001,.01,.05, .1, 1),`	16179	`+ cutpoints = c(0, .001,.01,.05, .1, 1),`
Line 16957...		Line 16957...
16957	`search in [0,2] ... extended to [-1073.74, 2.14748e+07] in 30 steps`	16957	`search in [0,2] ... extended to [-1073.74, 2.14748e+07] in 30 steps`
16958	`>`	16958	`>`
16959	`> ## Nonsense example (must give an error):`	16959	`> ## Nonsense example (must give an error):`
16960	`> tools::assertCondition( uniroot(function(x) 1, 0:1, extendInt="yes"),`	16960	`> tools::assertCondition( uniroot(function(x) 1, 0:1, extendInt="yes"),`
16961	`+ "error", verbose=TRUE)`	16961	`+ "error", verbose=TRUE)`
16962	`assertCondition: caught "error"`	16962	`assertCondition: caught “error”`
16963	`>`	16963	`>`
16964	`> ## Convergence checking :`	16964	`> ## Convergence checking :`
16965	`> sinc <- function(x) ifelse(x == 0, 1, sin(x)/x)`	16965	`> sinc <- function(x) ifelse(x == 0, 1, sin(x)/x)`
16966	`> curve(sinc, -6,18); abline(h=0,v=0, lty=3, col=adjustcolor("gray", 0.8))`	16966	`> curve(sinc, -6,18); abline(h=0,v=0, lty=3, col=adjustcolor("gray", 0.8))`
16967	`> ## Don't show:`	16967	`> ## Don't show:`
Line 17058...		Line 17058...
17058	`Coefficients:`	17058	`Coefficients:`
17059	`Estimate Std. Error t value Pr(>\|t\|)`	17059	`Estimate Std. Error t value Pr(>\|t\|)`
17060	`groupCtl 5.0320 0.2202 22.85 9.55e-15 ***`	17060	`groupCtl 5.0320 0.2202 22.85 9.55e-15 ***`
17061	`groupTrt 4.6610 0.2202 21.16 3.62e-14 ***`	17061	`groupTrt 4.6610 0.2202 21.16 3.62e-14 ***`
17062	`---`	17062	`---`
17063	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	17063	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
17064		17064
17065	`Residual standard error: 0.6964 on 18 degrees of freedom`	17065	`Residual standard error: 0.6964 on 18 degrees of freedom`
17066	`Multiple R-squared: 0.9818, Adjusted R-squared: 0.9798`	17066	`Multiple R-squared: 0.9818, Adjusted R-squared: 0.9798`
17067	`F-statistic: 485.1 on 2 and 18 DF, p-value: < 2.2e-16`	17067	`F-statistic: 485.1 on 2 and 18 DF, p-value: < 2.2e-16`
17068		17068
Line 17797...		Line 17797...
17797	`>`	17797	`>`
17798	`>`	17798	`>`
17799	`>`	17799	`>`
17800	`> cleanEx()`	17800	`> cleanEx()`
17801		17801
17802	`detaching 'package:Matrix', 'package:lattice'`	17802	`detaching ‘package:Matrix’, ‘package:lattice’`
17803		17803
17804	`> nameEx("zC")`	17804	`> nameEx("zC")`
17805	`> ### * zC`	17805	`> ### * zC`
17806	`>`	17806	`>`
17807	`> flush(stderr()); flush(stdout())`	17807	`> flush(stderr()); flush(stdout())`
Line 17845...		Line 17845...
17845	`(Intercept) 29.278 3.162 9.260 2e-12 ***`	17845	`(Intercept) 29.278 3.162 9.260 2e-12 ***`
17846	`woolB -5.778 3.162 -1.827 0.0736 .`	17846	`woolB -5.778 3.162 -1.827 0.0736 .`
17847	`C(tension, base = 2)1 10.000 3.872 2.582 0.0128 *`	17847	`C(tension, base = 2)1 10.000 3.872 2.582 0.0128 *`
17848	`C(tension, base = 2)3 -4.722 3.872 -1.219 0.2284`	17848	`C(tension, base = 2)3 -4.722 3.872 -1.219 0.2284`
17849	`---`	17849	`---`
17850	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	17850	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
17851		17851
17852	`Residual standard error: 11.62 on 50 degrees of freedom`	17852	`Residual standard error: 11.62 on 50 degrees of freedom`
17853	`Multiple R-squared: 0.2691, Adjusted R-squared: 0.2253`	17853	`Multiple R-squared: 0.2691, Adjusted R-squared: 0.2253`
17854	`F-statistic: 6.138 on 3 and 50 DF, p-value: 0.00123`	17854	`F-statistic: 6.138 on 3 and 50 DF, p-value: 0.00123`
17855		17855
Line 17877...		Line 17877...
17877	`agegp^4 0.06668 0.30776 0.217 0.82848`	17877	`agegp^4 0.06668 0.30776 0.217 0.82848`
17878	`agegp^5 -0.20288 0.19523 -1.039 0.29872`	17878	`agegp^5 -0.20288 0.19523 -1.039 0.29872`
17879	`C(tobgp, , 1).L 0.58501 0.18331 3.191 0.00142 **`	17879	`C(tobgp, , 1).L 0.58501 0.18331 3.191 0.00142 **`
17880	`C(alcgp, , 1).L 1.46034 0.18899 7.727 1.10e-14 ***`	17880	`C(alcgp, , 1).L 1.46034 0.18899 7.727 1.10e-14 ***`
17881	`---`	17881	`---`
17882	`Signif. codes: 0 '*' 0.001 '' 0.01 '*' 0.05 '.' 0.1 ' ' 1`	17882	`Signif. codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1`
17883		17883
17884	`(Dispersion parameter for binomial family taken to be 1)`	17884	`(Dispersion parameter for binomial family taken to be 1)`
17885		17885
17886	`Null deviance: 227.241 on 87 degrees of freedom`	17886	`Null deviance: 227.241 on 87 degrees of freedom`
17887	`Residual deviance: 59.277 on 80 degrees of freedom`	17887	`Residual deviance: 59.277 on 80 degrees of freedom`
Line 17895...		Line 17895...
17895	`> base::options(contrasts = c(unordered = "contr.treatment",ordered = "contr.poly"))`	17895	`> base::options(contrasts = c(unordered = "contr.treatment",ordered = "contr.poly"))`
17896	`> ### * <FOOTER>`	17896	`> ### * <FOOTER>`
17897	`> ###`	17897	`> ###`
17898	`> options(digits = 7L)`	17898	`> options(digits = 7L)`
17899	`> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")`	17899	`> base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")`
17900	`Time elapsed: 7.043 0.31 7.584 0 0`	17900	`Time elapsed: 6.681 0.143 6.848 0 0`
17901	`> grDevices::dev.off()`	17901	`> grDevices::dev.off()`
17902	`null device`	17902	`null device`
17903	`1`	17903	`1`
17904	`> ###`	17904	`> ###`
17905	`> ### Local variables: ***`	17905	`> ### Local variables: ***`

The R Project SVN R

(root)/trunk/tests/Examples/stats-Ex.Rout.save – Rev 63205 → 63207