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library(nlme)if (requireNamespace("MASS")) {## Example 1 --- was ./update.R ---data(petrol, package = 'MASS')Petrol <- petrolPetrol[, 2:5] <- scale(Petrol[, 2:5], scale = FALSE)pet3.lme <- lme(Y ~ SG + VP + V10 + EP,random = ~ 1 | No, data = Petrol, method="ML")upet3 <- update(pet3.lme, Y ~ SG + VP + V10)upet3vc3 <- VarCorr(upet3)upet2 <- lme(Y ~ SG + VP + V10, random = ~ 1 | No, data = Petrol, method = "ML")stopifnot(all.equal(upet3, upet2, tol = 1e-15),all.equal(fixef(upet3),c("(Intercept)" = 19.659375, SG = 0.125045632,VP = 2.27818601, V10 = 0.0672413592), tol = 1e-8)# 1e-9,all.equal(as.numeric(vc3[,"StdDev"]),c(0.00029397, 9.69657845), tol=1e-6))}## Example 2 ---data(Assay)as1 <- lme(logDens~sample*dilut, data=Assay,random=pdBlocked(list(pdIdent(~1),pdIdent(~sample-1),pdIdent(~dilut-1))))as1s <- update(as1, random=pdCompSymm(~sample-1))(an.1s <- anova(as1, as1s)) # non significantstopifnot(all.equal(drop(data.matrix(an.1s[2,-1])),c(Model = 2, df = 33, AIC = -10.958851, BIC = 35.280663,logLik = 38.479425, Test = 2,L.Ratio = 0.11370211, `p-value` = 0.73596807), tol=8e-8))as1S <- update(as1, . ~ sample+dilut) # dropping FE interactiontools::assertWarning(anova(as1, as1S))# REML not ok for different FE.as1M <- update(as1, method = "ML")as1SM <- update(as1S, method = "ML")(anM <- anova(as1M, as1SM)) # anova() OK: comparing MLE fits## ==> significant: P ~= 0.0054stopifnot(all.equal(drop(data.matrix(anM[2,])[,-(1:2)]),c(df = 14, AIC = -169.588248, BIC = -140.267424, logLik = 98.7941241,Test = 2, L.Ratio = 39.7345188, `p-value` = 0.0053958561),tol = 8e-8))