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Type 'q()' to quit R. > library(nlme) > > op <- options(digits = 3) # reduce rounding differences > > Ovary[c(1,272), 2] <- NA > fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary, + correlation = corAR1(form = ~ 1 | Mare), na.action=na.exclude) > fitted(fm1) 1 2 3 4 5 6 7 8 9 10 11 12 13 NA 12.86 12.06 11.27 10.55 9.96 9.54 9.34 9.36 9.60 10.05 10.67 11.41 14 15 16 17 18 19 20 21 22 23 24 25 26 12.21 13.00 13.71 14.31 14.72 14.93 14.91 14.66 14.21 13.59 12.86 12.06 11.27 27 28 29 30 31 32 33 34 35 36 37 38 39 10.55 9.96 9.54 13.79 13.01 12.14 11.27 10.49 9.86 9.46 9.32 9.45 9.85 40 41 42 43 44 45 46 47 48 49 50 51 52 10.47 11.26 12.13 13.00 13.78 14.41 14.81 14.95 14.81 14.41 13.79 13.01 12.14 53 54 55 56 57 58 59 60 61 62 63 64 65 11.27 10.49 9.86 9.46 13.90 13.10 12.19 11.27 10.45 9.81 9.42 9.32 9.53 66 67 68 69 70 71 72 73 74 75 76 77 78 10.03 10.75 11.62 12.54 13.42 14.17 14.69 14.93 14.87 14.52 13.90 13.10 12.19 79 80 81 82 83 84 85 86 87 88 89 90 91 11.27 10.45 9.81 9.42 13.59 12.86 12.06 11.27 10.55 9.96 9.54 9.34 9.36 92 93 94 95 96 97 98 99 100 101 102 103 104 9.60 10.05 10.67 11.41 12.21 13.00 13.71 14.31 14.72 14.93 14.91 14.66 14.21 105 106 107 108 109 110 111 112 113 114 115 116 117 13.59 12.86 12.06 11.27 10.55 9.96 9.54 13.59 12.86 12.06 11.27 10.55 9.96 118 119 120 121 122 123 124 125 126 127 128 129 130 9.54 9.34 9.36 9.60 10.05 10.67 11.41 12.21 13.00 13.71 14.31 14.72 14.93 131 132 133 134 135 136 137 138 139 140 141 142 143 14.91 14.66 14.21 13.59 12.86 12.06 11.27 10.55 9.96 9.54 13.59 12.86 12.06 144 145 146 147 148 149 150 151 152 153 154 155 156 11.27 10.55 9.96 9.54 9.34 9.36 9.60 10.05 10.67 11.41 12.21 13.00 13.71 157 158 159 160 161 162 163 164 165 166 167 168 169 14.31 14.72 14.93 14.91 14.66 14.21 13.59 12.86 12.06 11.27 10.55 9.96 9.54 170 171 172 173 174 175 176 177 178 179 180 181 182 13.79 13.01 12.14 11.27 10.49 9.86 9.46 9.32 9.45 9.85 10.47 11.26 12.13 183 184 185 186 187 188 189 190 191 192 193 194 195 13.00 13.78 14.41 14.81 14.95 14.81 14.41 13.79 13.01 12.14 11.27 10.49 9.86 196 197 198 199 200 201 202 203 204 205 206 207 208 9.46 13.42 12.73 11.99 11.27 10.61 10.05 9.63 9.38 9.32 9.45 9.77 10.24 209 210 211 212 213 214 215 216 217 218 219 220 221 10.85 11.54 12.27 13.00 13.66 14.22 14.64 14.88 14.94 14.81 14.50 14.02 13.42 222 223 224 225 226 227 228 229 230 231 232 233 234 12.73 11.99 11.27 10.61 10.05 9.63 14.02 13.19 12.24 11.27 10.41 9.75 9.38 235 236 237 238 239 240 241 242 243 244 245 246 247 9.35 9.64 10.24 11.07 12.03 13.00 13.86 14.52 14.88 14.92 14.62 14.02 13.19 248 249 250 251 252 253 254 255 256 257 258 259 260 12.24 11.27 10.41 9.75 9.38 13.59 12.86 12.06 11.27 10.55 9.96 9.54 9.34 261 262 263 264 265 266 267 268 269 270 271 272 273 9.36 9.60 10.05 10.67 11.41 12.21 13.00 13.71 14.31 14.72 14.93 NA 14.66 274 275 276 277 278 279 280 281 282 283 284 285 286 14.21 13.59 12.86 12.06 11.27 10.55 9.96 9.54 13.79 13.01 12.14 11.27 10.49 287 288 289 290 291 292 293 294 295 296 297 298 299 9.86 9.46 9.32 9.45 9.85 10.47 11.26 12.13 13.00 13.78 14.41 14.81 14.95 300 301 302 303 304 305 306 307 308 14.81 14.41 13.79 13.01 12.14 11.27 10.49 9.86 9.46 attr(,"label") [1] "Fitted values" > residuals(fm1) 1 2 3 4 5 6 7 8 NA 2.1439 6.9394 4.7290 2.4488 0.0405 2.4560 4.6618 9 10 11 12 13 14 15 16 3.6412 10.3959 11.9456 4.3270 6.5900 4.7945 1.0049 4.2851 17 18 19 20 21 22 23 24 -0.3066 1.2779 2.0720 3.0927 3.3380 2.7883 0.4069 -0.8561 25 26 27 28 29 30 31 32 -0.0606 2.7290 -0.5512 1.0405 6.4560 -7.7936 -7.0102 -4.1410 33 34 35 36 37 38 39 40 -4.2710 5.5146 0.1390 3.5409 -0.3189 -2.4542 -3.8517 -2.4725 41 42 43 44 45 46 47 48 -3.2559 -6.1251 -4.9951 -6.7808 -5.4051 -8.8070 -10.9472 -9.8119 49 50 51 52 53 54 55 56 -6.4144 -2.7936 -0.0102 -2.1410 -5.2710 -3.4854 -3.8610 -4.4591 57 58 59 60 61 62 63 64 -0.9042 -2.0982 -2.1875 -5.2710 -2.4479 -3.8074 -0.4189 -0.3245 65 66 67 68 69 70 71 72 0.4655 -2.0261 3.2540 1.3838 1.4576 2.5757 5.8338 6.3122 73 74 75 76 77 78 79 80 10.0674 8.1260 4.4817 8.0958 2.9018 8.8125 7.7290 9.5521 81 82 83 84 85 86 87 88 7.1926 14.5811 -4.5931 -3.8561 -5.0606 -5.2710 -3.5512 -3.9595 89 90 91 92 93 94 95 96 -8.5440 -8.3382 -8.3588 -4.6041 -4.0544 -7.6730 -6.4100 -9.2055 97 98 99 100 101 102 103 104 -6.9951 -5.7149 -8.3066 -9.7221 -8.9280 -6.9073 -3.6620 -0.2117 105 106 107 108 109 110 111 112 -5.5931 -3.8561 -2.0606 -4.2710 -3.5512 -3.9595 1.4560 -3.5931 113 114 115 116 117 118 119 120 -0.8561 -0.0606 5.7290 -1.5512 0.0405 -6.5440 2.6618 3.6412 121 122 123 124 125 126 127 128 -0.6041 -6.0544 -3.6730 -7.4100 -0.2055 1.0049 -1.7149 0.6934 129 130 131 132 133 134 135 136 2.2779 0.0720 -1.9073 3.3380 4.7883 -0.5931 -3.8561 -0.0606 137 138 139 140 141 142 143 144 -3.2710 -0.5512 -4.9595 4.4560 2.4069 4.1439 0.9394 5.7290 145 146 147 148 149 150 151 152 4.4488 -0.9595 -1.5440 -4.3382 -0.3588 -1.6041 -2.0544 2.3270 153 154 155 156 157 158 159 160 2.5900 0.7945 1.0049 0.2851 -3.3066 2.2779 6.0720 6.0927 161 162 163 164 165 166 167 168 6.3380 5.7883 3.4069 5.1439 9.9394 -1.2710 0.4488 1.0405 169 170 171 172 173 174 175 176 2.4560 4.2064 -0.0102 1.8590 0.7290 0.5146 -1.8610 -4.4591 177 178 179 180 181 182 183 184 -1.3189 0.5458 1.1483 -0.4725 0.7441 -2.1251 -3.9951 -1.7808 185 186 187 188 189 190 191 192 -0.4051 1.1930 -1.9472 -3.8119 -1.4144 -0.7936 -2.0102 -1.1410 193 194 195 196 197 198 199 200 -3.2710 3.5146 -5.8610 -2.4591 -0.4177 -3.7259 3.0063 3.7290 201 202 203 204 205 206 207 208 1.3930 -2.0471 0.3708 -3.3821 -0.3224 -1.4542 0.2314 -4.2441 209 210 211 212 213 214 215 216 -2.8484 1.4598 -0.2724 -0.9951 1.3409 6.7809 10.3631 6.1159 217 218 219 220 221 222 223 224 6.0562 9.1881 5.5025 5.9780 4.5823 7.2741 8.0063 7.7290 225 226 227 228 229 230 231 232 1.3930 -3.0471 -1.6292 -4.0220 0.8054 -0.2392 -1.2710 -3.4068 233 234 235 236 237 238 239 240 2.2493 0.6179 -1.3452 0.3554 4.7559 3.9285 -0.0269 6.0049 241 242 243 244 245 246 247 248 1.1406 1.4846 0.1159 2.0791 -0.6215 1.9780 1.8054 -1.2392 249 250 251 252 253 254 255 256 -1.2710 -3.4067 -5.7507 -1.3821 -2.5931 3.1439 2.9394 0.7290 257 258 259 260 261 262 263 264 0.4488 -3.9595 1.4560 2.6618 1.6412 6.3959 4.9456 0.3270 265 266 267 268 269 270 271 272 -4.4100 1.7945 7.0049 8.2851 8.6934 6.2779 6.0720 NA 273 274 275 276 277 278 279 280 7.3380 7.7883 3.4069 4.1439 4.9394 5.7290 3.4488 2.0405 281 282 283 284 285 286 287 288 1.4560 -4.7936 -5.0102 -4.1410 -3.2710 -2.4854 -3.8610 -2.4591 289 290 291 292 293 294 295 296 -1.3189 0.5458 0.1483 3.5275 1.7441 -4.1251 -4.9951 -5.7808 297 298 299 300 301 302 303 304 -5.4051 1.1930 -2.9472 -4.8119 -2.4144 -1.7936 -4.0102 -6.1410 305 306 307 308 -2.2710 -3.4854 -4.8610 -4.4591 attr(,"std") [1] NA 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [16] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [31] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [46] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [61] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [76] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [91] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [106] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [121] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [136] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [151] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [166] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [181] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [196] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [211] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [226] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [241] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [256] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [271] 4.58 NA 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [286] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 [301] 4.58 4.58 4.58 4.58 4.58 4.58 4.58 4.58 attr(,"label") [1] "Residuals" > summary(fm1) Generalized least squares fit by REML Model: follicles ~ sin(2 * pi * Time) + cos(2 * pi * Time) Data: Ovary AIC BIC logLik 1560 1579 -775 Correlation Structure: AR(1) Formula: ~1 | Mare Parameter estimate(s): Phi 0.75 Coefficients: Value Std.Error t-value p-value (Intercept) 12.13 0.657 18.46 0.000 sin(2 * pi * Time) -2.68 0.644 -4.16 0.000 cos(2 * pi * Time) -0.86 0.690 -1.25 0.213 Correlation: (Intr) s(*p*T sin(2 * pi * Time) -0.007 cos(2 * pi * Time) -0.295 0.003 Standardized residuals: Min Q1 Med Q3 Max -2.3897 -0.7565 -0.0132 0.6396 3.1830 Residual standard error: 4.58 Degrees of freedom: 306 total; 303 residual > > Orthodont[100:102, 2] <- NA > fm2 <- lme(distance ~ age + Sex, data = Orthodont, random = ~ 1, + na.action=na.exclude) > fitted(fm2, 0:1) fixed Subject 1 23.0 25.4 2 24.3 26.7 3 25.6 28.0 4 27.0 29.4 5 23.0 21.6 6 24.3 22.9 7 25.6 24.3 8 27.0 25.6 9 23.0 22.3 10 24.3 23.7 11 25.6 25.0 12 27.0 26.4 13 23.0 24.4 14 24.3 25.7 15 25.6 27.1 16 27.0 28.4 17 23.0 21.3 18 24.3 22.6 19 25.6 23.9 20 27.0 25.3 21 23.0 24.2 22 24.3 25.5 23 25.6 26.9 24 27.0 28.2 25 23.0 21.9 26 24.3 23.2 27 25.6 24.6 28 27.0 25.9 29 23.0 22.0 30 24.3 23.4 31 25.6 24.7 32 27.0 26.0 33 23.0 23.1 34 24.3 24.4 35 25.6 25.8 36 27.0 27.1 37 23.0 26.9 38 24.3 28.2 39 25.6 29.5 40 27.0 30.9 41 23.0 21.8 42 24.3 23.1 43 25.6 24.5 44 27.0 25.8 45 23.0 22.3 46 24.3 23.7 47 25.6 25.0 48 27.0 26.4 49 23.0 22.3 50 24.3 23.7 51 25.6 25.0 52 27.0 26.4 53 23.0 22.9 54 24.3 24.2 55 25.6 25.6 56 27.0 26.9 57 23.0 23.7 58 24.3 25.1 59 25.6 26.4 60 27.0 27.8 61 23.0 21.3 62 24.3 22.6 63 25.6 23.9 64 27.0 25.3 65 20.7 19.5 66 22.0 20.9 67 23.4 22.2 68 24.7 23.6 69 20.7 20.9 70 22.0 22.3 71 23.4 23.6 72 24.7 25.0 73 20.7 21.6 74 22.0 22.9 75 23.4 24.3 76 24.7 25.6 77 20.7 22.6 78 22.0 23.9 79 23.4 25.2 80 24.7 26.6 81 20.7 20.6 82 22.0 22.0 83 23.4 23.3 84 24.7 24.6 85 20.7 19.3 86 22.0 20.7 87 23.4 22.0 88 24.7 23.4 89 20.7 20.9 90 22.0 22.3 91 23.4 23.6 92 24.7 25.0 93 20.7 21.3 94 22.0 22.6 95 23.4 24.0 96 24.7 25.3 97 20.7 19.8 98 22.0 21.2 99 23.4 22.5 100 NA NA 101 NA NA 102 NA NA 103 23.4 19.7 104 24.7 21.1 105 20.7 23.9 106 22.0 25.2 107 23.4 26.5 108 24.7 27.9 > fitted(fm2) M01 M01 M01 M01 M02 M02 M02 M02 M03 M03 M03 M03 M04 M04 M04 M04 25.4 26.7 28.0 29.4 21.6 22.9 24.3 25.6 22.3 23.7 25.0 26.4 24.4 25.7 27.1 28.4 M05 M05 M05 M05 M06 M06 M06 M06 M07 M07 M07 M07 M08 M08 M08 M08 21.3 22.6 23.9 25.3 24.2 25.5 26.9 28.2 21.9 23.2 24.6 25.9 22.0 23.4 24.7 26.0 M09 M09 M09 M09 M10 M10 M10 M10 M11 M11 M11 M11 M12 M12 M12 M12 23.1 24.4 25.8 27.1 26.9 28.2 29.5 30.9 21.8 23.1 24.5 25.8 22.3 23.7 25.0 26.4 M13 M13 M13 M13 M14 M14 M14 M14 M15 M15 M15 M15 M16 M16 M16 M16 22.3 23.7 25.0 26.4 22.9 24.2 25.6 26.9 23.7 25.1 26.4 27.8 21.3 22.6 23.9 25.3 F01 F01 F01 F01 F02 F02 F02 F02 F03 F03 F03 F03 F04 F04 F04 F04 19.5 20.9 22.2 23.6 20.9 22.3 23.6 25.0 21.6 22.9 24.3 25.6 22.6 23.9 25.2 26.6 F05 F05 F05 F05 F06 F06 F06 F06 F07 F07 F07 F07 F08 F08 F08 F08 20.6 22.0 23.3 24.6 19.3 20.7 22.0 23.4 20.9 22.3 23.6 25.0 21.3 22.6 24.0 25.3 F09 F09 F09 F10 F10 F11 F11 F11 F11 19.8 21.2 22.5 NA NA NA 19.7 21.1 23.9 25.2 26.5 27.9 attr(,"label") [1] "Fitted values (mm)" > residuals(fm2, 0:1) fixed Subject 1 3.0453 0.64827 2 0.7026 -1.69443 3 3.3599 0.96286 4 4.0172 1.62016 5 -1.4547 -0.08111 6 -1.7974 -0.42382 7 -2.6401 -1.26652 8 -0.4828 0.89078 9 0.0453 0.66476 10 -1.7974 -1.17794 11 -1.6401 -1.02064 12 0.5172 1.13665 13 2.5453 1.11786 14 3.2026 1.77515 15 0.8599 -0.56755 16 0.0172 -1.41025 17 -2.9547 -1.25792 18 -0.7974 0.89938 19 -3.1401 -1.44332 20 -0.9828 0.71397 21 1.5453 0.33332 22 1.2026 -0.00938 23 1.3599 0.14791 24 1.5172 0.30521 25 -0.9547 0.09569 26 -2.2974 -1.24701 27 -1.1401 -0.08972 28 -0.4828 0.56758 29 1.0453 1.98796 30 -2.7974 -1.85474 31 -1.1401 -0.19745 32 -1.4828 -0.54015 33 0.0453 -0.08936 34 -3.7974 -3.93206 35 5.3599 5.22523 36 -0.9828 -1.11747 37 4.5453 0.64002 38 3.7026 -0.20268 39 5.3599 1.45461 40 4.5172 0.61191 41 0.0453 1.20342 42 -1.2974 -0.13928 43 -2.1401 -0.98198 44 -1.9828 -0.82469 45 -1.4547 -0.83524 46 -0.7974 -0.17794 47 -1.6401 -1.02064 48 1.0172 1.63665 49 -5.9547 -5.33524 50 0.2026 0.82206 51 0.3599 0.97936 52 2.5172 3.13665 53 -0.4547 -0.37390 54 1.2026 1.28340 55 -0.1401 -0.05930 56 -0.9828 -0.90201 57 0.0453 -0.73575 58 0.2026 -0.57846 59 0.3599 -0.42116 60 3.0172 2.23614 61 -0.9547 0.74208 62 -2.7974 -1.10062 63 -2.1401 -0.44332 64 -1.9828 -0.28603 65 0.3135 1.45594 66 -2.0292 -0.88676 67 -1.8719 -0.72947 68 -1.7146 -0.57217 69 0.3135 0.05543 70 -0.5292 -0.78728 71 0.6281 0.37002 72 0.7854 0.52732 73 -0.1865 -1.09097 74 1.9708 1.06633 75 1.1281 0.22363 76 1.2854 0.38092 77 2.8135 0.93945 78 2.4708 0.59674 79 1.6281 -0.24596 80 1.7854 -0.08866 81 0.8135 0.87862 82 0.9708 1.03592 83 -0.8719 -0.80678 84 -1.2146 -1.14949 85 -0.6865 0.67141 86 -1.0292 0.32870 87 -2.3719 -1.01400 88 -2.2146 -0.85670 89 0.8135 0.55543 90 0.4708 0.21272 91 -0.3719 -0.62998 92 0.2854 0.02732 93 2.3135 1.73223 94 0.9708 0.38953 95 0.1281 -0.45318 96 -0.7146 -1.29588 97 -0.6865 0.16148 98 -1.0292 -0.18122 99 -1.3719 -0.52392 100 NA NA 101 NA NA 102 NA NA 103 -4.3719 -0.74222 104 -5.2146 -1.58492 105 3.8135 0.64666 106 2.9708 -0.19604 107 4.6281 1.46126 108 3.2854 0.11855 > round(residuals(fm2), 2) M01 M01 M01 M01 M02 M02 M02 M02 M03 M03 M03 M03 M04 0.65 -1.69 0.96 1.62 -0.08 -0.42 -1.27 0.89 0.66 -1.18 -1.02 1.14 1.12 M04 M04 M04 M05 M05 M05 M05 M06 M06 M06 M06 M07 M07 1.78 -0.57 -1.41 -1.26 0.90 -1.44 0.71 0.33 -0.01 0.15 0.31 0.10 -1.25 M07 M07 M08 M08 M08 M08 M09 M09 M09 M09 M10 M10 M10 -0.09 0.57 1.99 -1.85 -0.20 -0.54 -0.09 -3.93 5.23 -1.12 0.64 -0.20 1.45 M10 M11 M11 M11 M11 M12 M12 M12 M12 M13 M13 M13 M13 0.61 1.20 -0.14 -0.98 -0.82 -0.84 -0.18 -1.02 1.64 -5.34 0.82 0.98 3.14 M14 M14 M14 M14 M15 M15 M15 M15 M16 M16 M16 M16 F01 -0.37 1.28 -0.06 -0.90 -0.74 -0.58 -0.42 2.24 0.74 -1.10 -0.44 -0.29 1.46 F01 F01 F01 F02 F02 F02 F02 F03 F03 F03 F03 F04 F04 -0.89 -0.73 -0.57 0.06 -0.79 0.37 0.53 -1.09 1.07 0.22 0.38 0.94 0.60 F04 F04 F05 F05 F05 F05 F06 F06 F06 F06 F07 F07 F07 -0.25 -0.09 0.88 1.04 -0.81 -1.15 0.67 0.33 -1.01 -0.86 0.56 0.21 -0.63 F07 F08 F08 F08 F08 F09 F09 F09 F10 F10 0.03 1.73 0.39 -0.45 -1.30 0.16 -0.18 -0.52 NA NA NA -0.74 -1.58 F11 F11 F11 F11 0.65 -0.20 1.46 0.12 attr(,"label") [1] "Residuals (mm)" > summary(fm2) Linear mixed-effects model fit by REML Data: Orthodont AIC BIC logLik 437 450 -213 Random effects: Formula: ~1 | Subject (Intercept) Residual StdDev: 1.8 1.44 Fixed effects: distance ~ age + Sex Value Std.Error DF t-value p-value (Intercept) 17.58 0.850 77 20.68 0.0000 age 0.67 0.064 77 10.56 0.0000 SexFemale -2.27 0.762 25 -2.98 0.0064 Correlation: (Intr) age age -0.822 SexFemale -0.357 -0.006 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -3.7079 -0.5471 -0.0564 0.4666 3.6314 Number of Observations: 105 Number of Groups: 27 > > Soybean[1:5, "Time"] <- NA > fm3 <- gnls(weight ~ SSlogis(Time, Asym, xmid, scal), Soybean, + weights = varPower(), na.action=na.exclude) > fitted(fm3) 1 2 3 4 5 6 7 8 9 10 11 NA NA NA NA NA 7.047 10.958 14.082 15.894 16.756 0.120 12 13 14 15 16 17 18 19 20 21 22 0.298 0.726 1.708 3.724 7.047 10.958 15.894 16.756 0.120 0.298 0.726 23 24 25 26 27 28 29 30 31 32 33 1.708 3.724 7.047 10.958 14.082 15.894 16.756 0.120 0.298 0.726 1.708 34 35 36 37 38 39 40 41 42 43 44 3.724 7.047 10.958 14.082 15.894 16.756 0.120 0.298 0.726 1.708 3.724 45 46 47 48 49 50 51 52 53 54 55 7.047 10.958 15.894 0.120 0.298 0.726 1.708 3.724 7.047 10.958 14.082 56 57 58 59 60 61 62 63 64 65 66 15.894 16.756 0.120 0.298 0.726 1.708 3.724 7.047 10.958 15.894 16.756 67 68 69 70 71 72 73 74 75 76 77 0.120 0.298 0.726 1.708 3.724 7.047 10.958 14.082 15.894 16.756 0.120 78 79 80 81 82 83 84 85 86 87 88 0.298 0.726 1.708 3.724 7.047 10.958 14.082 15.894 16.756 0.120 0.298 89 90 91 92 93 94 95 96 97 98 99 0.726 1.708 3.724 7.047 10.958 14.082 15.894 16.756 0.120 0.298 0.726 100 101 102 103 104 105 106 107 108 109 110 1.708 3.724 7.047 10.958 14.082 15.894 16.756 0.120 0.298 0.726 1.708 111 112 113 114 115 116 117 118 119 120 121 3.724 7.047 10.958 14.082 15.894 16.756 0.120 0.298 0.726 1.708 3.724 122 123 124 125 126 127 128 129 130 131 132 7.047 10.958 14.082 15.894 16.756 0.120 0.298 0.726 1.708 3.724 7.047 133 134 135 136 137 138 139 140 141 142 143 10.958 14.082 15.894 16.756 0.120 0.298 0.726 1.708 3.724 7.047 10.958 144 145 146 147 148 149 150 151 152 153 154 14.082 15.894 16.756 0.120 0.298 0.726 1.708 3.724 7.047 10.958 14.082 155 156 157 158 159 160 161 162 163 164 165 15.894 16.756 0.120 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.120 166 167 168 169 170 171 172 173 174 175 176 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.120 0.262 0.640 1.517 177 178 179 180 181 182 183 184 185 186 187 3.355 10.419 15.706 17.127 0.120 0.262 0.640 1.517 3.355 10.419 15.706 188 189 190 191 192 193 194 195 196 197 198 17.127 0.120 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.120 0.262 199 200 201 202 203 204 205 206 207 208 209 0.640 1.517 3.355 10.419 15.706 17.127 0.120 0.262 0.640 1.517 3.355 210 211 212 213 214 215 216 217 218 219 220 10.419 15.706 17.127 0.120 0.262 0.640 1.517 3.355 10.419 15.706 17.127 221 222 223 224 225 226 227 228 229 230 231 0.120 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.120 0.262 0.640 232 233 234 235 236 237 238 239 240 241 242 1.517 3.355 10.419 15.706 17.127 0.120 0.262 0.640 1.517 3.355 10.419 243 244 245 246 247 248 249 250 251 252 253 15.706 17.127 0.120 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.120 254 255 256 257 258 259 260 261 262 263 264 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.120 0.262 0.640 1.517 265 266 267 268 269 270 271 272 273 274 275 3.355 10.419 15.706 17.127 0.120 0.262 0.640 1.517 3.355 10.419 15.706 276 277 278 279 280 281 282 283 284 285 286 17.127 0.120 0.262 0.640 1.517 3.355 10.419 15.706 17.127 0.137 0.385 287 288 289 290 291 292 293 294 295 296 297 0.932 2.157 4.121 8.166 14.418 16.897 0.137 0.385 0.932 2.157 4.121 298 299 300 301 302 303 304 305 306 307 308 8.166 14.418 16.897 0.137 0.385 0.932 2.157 4.121 8.166 14.418 16.897 309 310 311 312 313 314 315 316 317 318 319 0.137 0.385 0.932 2.157 4.121 8.166 14.418 16.897 0.137 0.385 0.932 320 321 322 323 324 325 326 327 328 329 330 2.157 4.121 8.166 14.418 16.897 0.137 0.385 0.932 2.157 4.121 8.166 331 332 333 334 335 336 337 338 339 340 341 14.418 16.897 0.137 0.385 0.932 2.157 4.121 8.166 14.418 16.897 0.137 342 343 344 345 346 347 348 349 350 351 352 0.385 0.932 2.157 4.121 8.166 14.418 16.897 0.137 0.385 0.932 2.157 353 354 355 356 357 358 359 360 361 362 363 4.121 8.166 14.418 16.897 0.137 0.385 0.932 2.157 4.121 8.166 14.418 364 365 366 367 368 369 370 371 372 373 374 16.897 0.137 0.385 0.932 2.157 4.121 8.166 14.418 16.897 0.137 0.385 375 376 377 378 379 380 381 382 383 384 385 0.932 2.157 4.121 8.166 14.418 16.897 0.137 0.385 0.932 2.157 4.121 386 387 388 389 390 391 392 393 394 395 396 8.166 14.418 16.897 0.137 0.385 0.932 2.157 4.121 8.166 14.418 16.897 397 398 399 400 401 402 403 404 405 406 407 0.137 0.385 0.932 2.157 4.121 8.166 14.418 16.897 0.137 0.385 0.932 408 409 410 411 412 2.157 4.121 8.166 14.418 16.897 attr(,"label") [1] "Fitted values (g)" > residuals(fm3) 1 2 3 4 5 6 7 8 NA NA NA NA NA -0.81724 -2.24772 -0.73203 9 10 11 12 13 14 15 16 0.44774 0.99485 -0.01627 -0.02870 0.05209 0.41153 -0.79366 -1.75724 17 18 19 20 21 22 23 24 -1.45772 1.07274 0.99072 -0.01227 -0.00670 -0.05891 0.34153 0.08634 25 26 27 28 29 30 31 32 -0.91724 -0.67772 3.99797 4.28854 5.05482 -0.01527 0.00130 0.11809 33 34 35 36 37 38 39 40 -0.38847 -1.48366 -2.36724 -2.13772 1.00797 -1.23396 -2.75138 -0.01927 41 42 43 44 45 46 47 48 -0.02470 0.12209 0.24153 1.04634 -1.03724 -1.04772 3.36834 -0.01427 49 50 51 52 53 54 55 56 0.03930 -0.02691 -0.17847 0.14634 -1.44724 -1.52772 -0.35203 1.48684 57 58 59 60 61 62 63 64 3.17632 -0.01827 -0.02270 0.04109 -0.25847 0.22634 -2.10724 -1.31772 65 66 67 68 69 70 71 72 1.98604 0.96822 -0.01727 -0.02470 0.01609 -0.29847 -0.71366 -1.78724 73 74 75 76 77 78 79 80 -1.14772 -1.23203 2.32021 2.92402 0.01073 0.04030 -0.02491 -0.04847 81 82 83 84 85 86 87 88 0.52634 2.19276 1.19228 2.69797 0.03104 0.51632 0.00773 0.10630 89 90 91 92 93 94 95 96 0.17109 0.07153 0.18634 0.35276 -0.88772 4.77797 1.11774 10.61402 97 98 99 100 101 102 103 104 0.01073 0.08130 0.40009 0.73153 0.16634 -0.13724 1.53228 1.58797 105 106 107 108 109 110 111 112 7.86934 4.73482 0.03373 0.05930 0.45509 0.12153 0.98634 3.66276 113 114 115 116 117 118 119 120 -1.04772 1.42797 -0.93606 5.04402 0.01873 0.03030 0.20609 0.28153 121 122 123 124 125 126 127 128 -0.26366 -0.02724 0.83228 1.74797 0.02687 0.68572 0.01873 0.09130 129 130 131 132 133 134 135 136 0.36809 0.42153 0.31634 0.57276 1.52228 3.84797 -1.47226 13.51572 137 138 139 140 141 142 143 144 0.02473 0.06830 0.07309 -0.09847 -0.21366 -0.25724 -1.00772 0.45797 145 146 147 148 149 150 151 152 3.38604 5.81675 0.00973 0.05730 0.36409 0.57153 0.21634 -2.08724 153 154 155 156 157 158 159 160 -0.03772 -0.06203 2.10024 5.61482 -0.07327 -0.12571 -0.36726 -0.53373 161 162 163 164 165 166 167 168 -1.55813 -6.30167 -4.66844 -6.72407 -0.08527 -0.14971 -0.37209 -0.46373 169 170 171 172 173 174 175 176 -1.63980 -3.69048 -5.39225 -6.03907 -0.07627 -0.11571 -0.27959 -0.74206 177 178 179 180 181 182 183 184 -1.71313 -6.67048 -4.83058 -1.09990 -0.07127 -0.16471 -0.41259 -0.68373 185 186 187 188 189 190 191 192 -2.00080 -4.43048 -5.12058 -6.21597 -0.08127 -0.14071 -0.36842 -0.85873 193 194 195 196 197 198 199 200 -0.96480 -4.93548 -5.76891 -8.23907 -0.09127 -0.16971 -0.38909 -0.97539 201 202 203 204 205 206 207 208 -2.29313 -5.58881 -9.43391 -8.54407 -0.07927 -0.11671 -0.23476 -0.75706 209 210 211 212 213 214 215 216 -1.86147 -4.17048 -4.59388 -8.24740 -0.08227 -0.13471 -0.29992 -0.52306 217 218 219 220 221 222 223 224 -1.07313 -1.91281 -6.73225 -5.49540 -0.05027 -0.05371 -0.03926 0.38461 225 226 227 228 229 230 231 232 -0.38980 -2.27548 -0.00558 2.76090 -0.05227 -0.00971 -0.05959 0.49694 233 234 235 236 237 238 239 240 -0.68147 -1.61881 -1.22058 5.51590 -0.04327 -0.03771 -0.29876 0.22294 241 242 243 244 245 246 247 248 1.16920 1.23789 4.61112 4.27460 -0.02127 -0.06371 -0.14892 -0.31206 249 250 251 252 253 254 255 256 -0.55480 -3.05548 -0.56391 0.05927 -0.05227 -0.02971 -0.20409 -0.07373 257 258 259 260 261 262 263 264 -0.09480 -2.21048 3.70112 -1.46573 -0.05727 -0.05271 0.10074 -0.24873 265 266 267 268 269 270 271 272 0.53520 -1.32681 -1.21558 1.96760 0.01273 0.04129 0.47691 0.66294 273 274 275 276 277 278 279 280 0.18187 2.74119 0.08442 -2.35240 -0.03927 -0.00671 0.12474 -0.42373 281 282 283 284 285 286 287 288 -0.30313 -2.31381 8.71842 1.79090 -0.02776 -0.00104 0.23005 0.18344 289 290 291 292 293 294 295 296 -1.25117 1.37221 -1.73490 1.73667 -0.04196 -0.04654 -0.17329 0.36344 297 298 299 300 301 302 303 304 -1.60284 -3.04945 -5.84320 -2.72333 -0.04896 0.22830 0.38338 0.86511 305 306 307 308 309 310 311 312 1.72883 -0.74945 -3.08650 -0.01333 -0.04824 0.21180 0.14338 0.91844 313 314 315 316 317 318 319 320 -0.16284 -2.13279 -3.98153 0.90664 -0.03566 -0.00954 0.99005 0.05011 321 322 323 324 325 326 327 328 0.64383 0.97388 1.42180 1.21164 -0.02720 0.09846 0.37505 1.79844 329 330 331 332 333 334 335 336 0.18383 -0.13445 1.66513 2.67664 -0.03402 0.02963 0.73171 -0.76656 337 338 339 340 341 342 343 344 -1.11950 -1.32112 1.79180 2.17664 -0.06027 -0.01304 -0.18662 0.09011 345 346 347 348 349 350 351 352 0.37383 -2.49112 1.72680 2.03504 0.01178 0.30213 0.64005 1.65677 353 354 355 356 357 358 359 360 0.69050 3.48721 2.95850 1.00004 0.01680 0.20930 0.26838 0.98844 361 362 363 364 365 366 367 368 -0.31784 -0.74945 -0.83820 3.96334 -0.01280 0.36546 0.52671 3.60177 369 370 371 372 373 374 375 376 1.87550 0.80555 2.65350 0.92004 0.04150 0.49596 0.45005 1.47178 377 378 379 380 381 382 383 384 1.07217 -2.97612 1.36180 4.64501 0.00218 0.07096 0.65171 1.89844 385 386 387 388 389 390 391 392 0.38883 -0.00445 4.29680 1.05834 0.02574 0.38880 0.04338 1.35511 393 394 395 396 397 398 399 400 0.38883 -0.38279 3.70013 -0.94999 -0.02653 0.07113 0.43838 -0.01156 401 402 403 404 405 406 407 408 1.70883 0.63721 -2.18320 0.88834 0.00904 0.17880 0.54671 0.44511 409 410 411 412 2.22216 -2.03445 1.99350 0.05004 attr(,"std") [1] NA NA NA NA NA 2.0514 3.0228 3.7679 4.1905 4.3895 [11] 0.0575 0.1274 0.2786 0.5909 1.1714 2.0514 3.0228 4.1905 4.3895 0.0575 [21] 0.1274 0.2786 0.5909 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 [31] 0.1274 0.2786 0.5909 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 [41] 0.1274 0.2786 0.5909 1.1714 2.0514 3.0228 4.1905 0.0575 0.1274 0.2786 [51] 0.5909 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 [61] 0.5909 1.1714 2.0514 3.0228 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [71] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [81] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [91] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [101] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [111] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [121] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [131] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [141] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1274 0.2786 0.5909 [151] 1.1714 2.0514 3.0228 3.7679 4.1905 4.3895 0.0575 0.1137 0.2495 0.5324 [161] 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 [171] 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 [181] 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 [191] 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 [201] 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 [211] 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 [221] 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 [231] 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 [241] 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 [251] 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 [261] 0.0575 0.1137 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 [271] 0.2495 0.5324 1.0689 2.8919 4.1469 4.4749 0.0575 0.1137 0.2495 0.5324 [281] 1.0689 2.8919 4.1469 4.4749 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 [291] 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 [301] 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 [311] 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 [321] 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 [331] 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 [341] 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 [351] 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 [361] 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 [371] 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 [381] 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 [391] 0.3469 0.7251 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 [401] 1.2806 2.3348 3.8468 4.4219 0.0644 0.1596 0.3469 0.7251 1.2806 2.3348 [411] 3.8468 4.4219 attr(,"label") [1] "Residuals (g)" > summary(fm3) Generalized nonlinear least squares fit Model: weight ~ SSlogis(Time, Asym, xmid, scal) Data: Soybean AIC BIC logLik 987 1007 -489 Variance function: Structure: Power of variance covariate Formula: ~fitted(.) Parameter estimates: power 0.878 Coefficients: Value Std.Error t-value p-value Asym 17.4 0.525 33.1 0 xmid 51.9 0.598 86.8 0 scal 7.6 0.142 54.0 0 Correlation: Asym xmid xmid 0.788 scal 0.488 0.842 Standardized residuals: Min Q1 Med Q3 Max -2.3066 -0.6545 -0.0019 0.5012 4.9676 Residual standard error: 0.369 Degrees of freedom: 407 total; 404 residual > > options(op)# revert when this file is source()d > > proc.time() user system elapsed 0.302 0.033 0.399