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### Regression tests for which the printed output is the issue### May fail, e.g. by needing Recommended packagespostscript("reg-tests-3.ps")## str() for character & factors with NA (levels), and for Surv objects:ff <- factor(c(2:1, NA), exclude = NULL)str(levels(ff))str(ff)str(ordered(ff, exclude=NULL))if(require(survival)) {(sa <- Surv(aml$time, aml$status))str(sa)detach("package:survival")}## were different, the last one failed in 1.6.2 (at least)## lm.influence where hat[1] == 1if(require(MASS)) {fit <- lm(formula = 1000/MPG.city ~ Weight + Cylinders + Type + EngineSize + DriveTrain, data = Cars93)print(lm.influence(fit))## row 57 should have hat = 1 and resid=0.summary(influence.measures(fit))}## only last two cols in row 57 should be influential## PR#6640 Zero weights in plot.lmif(require(MASS)) {fm1 <- lm(time~dist, data=hills, weights=c(0,0,rep(1,33)))plot(fm1)}## gave warnings in 1.8.1## PR#7829 model.tables & replicationsif(require(MASS)) {oats.aov <- aov(Y ~ B + V + N + V:N, data=oats[-1,])model.tables(oats.aov, "means", cterms=c("N", "V:N"))}## wrong printed output in 2.1.0## drop1 on weighted lm() fitsif(require(MASS)) {hills.lm <- lm(time ~ 0 + dist + climb, data=hills, weights=1/dist^2)print(drop1(hills.lm))print(stats:::drop1.default(hills.lm))hills.lm2 <- lm(time/dist ~ 1 + I(climb/dist), data=hills)drop1(hills.lm2)}## quoted unweighted RSS etc in 2.2.1## tests of ISO C99 compliance (Windows fails without a workaround)sprintf("%g", 123456789)sprintf("%8g", 123456789)sprintf("%9.7g", 123456789)sprintf("%10.9g", 123456789)sprintf("%g", 12345.6789)sprintf("%10.9g", 12345.6789)sprintf("%10.7g", 12345.6789)sprintf("%.7g", 12345.6789)sprintf("%.5g", 12345.6789)sprintf("%.4g", 12345.6789)sprintf("%9.4g", 12345.6789)sprintf("%10.4g", 12345.6789)## Windows used e+008 etc prior to 2.3.0## weighted glm() fitsif(require(MASS)) {hills.glm <- glm(time ~ 0 + dist + climb, data=hills, weights=1/dist^2)print(AIC(hills.glm))print(extractAIC(hills.glm))print(drop1(hills.glm))stats:::drop1.default(hills.glm)}## wrong AIC() and drop1 prior to 2.3.0.## calculating no of signif digitsprint(1.001, digits=16)## 2.4.1 gave 1.001000000000000## 2.5.0 errs on the side of caution.## as.matrix.data.frame with coercionlibrary(survival)soa <- Surv(1:5, c(0, 0, 1, 0, 1))df.soa <- data.frame(soa)as.matrix(df.soa) # numeric resultdf.soac <- data.frame(soa, letters[1:5])as.matrix(df.soac) # character result## failed in 2.8.1