#### Tests psi(), chi(),... etc and tuning.psi, tuning.chi : library(robustbase) source(system.file("xtraR/plot-psiFun.R", package = "robustbase", mustWork=TRUE)) source(system.file("xtraR/test-tools.R", package = "robustbase")) # assert.EQ ### (1) Test the functions themselves -------------------------------- if(!dev.interactive(orNone=TRUE)) pdf("rob-psifns.pdf") ## Simple version, no error checking, no derivative, nothing: psiGGW <- function(x, a,b,c) { ifelse((ax <- abs(x)) < c, x, ifelse((ea <- -((ax-c)^b)/(2*a)) < -708.4, 0, x * exp(ea))) } assert.EQ(Mpsi (5:9, cc=c(0, a=1/8,b=2,c=1/8, NA), "GGW"), psiGGW(5:9, a=1/8,b=2,c=1/8), tol = 1e-13) ## Check that psi() |-> works; ditto for +-Inf, NA,.. cG <- c(-.5, 1, .95, NA) # one of the 6 "builtin"s d0 <- numeric() IoI <- c(-Inf, 0, Inf) NN <- c(NaN, NA) cGs <- list( c(-.4, 1.5, 0.85, NA) , c(-.4, 1.5 , 0.90, NA) , c(-.4, 1.5 , 0.95, NA) , c(-.4, 1.5, 0.975, NA) , c(-.4, 1.5, 0.99 , NA) , c(-.4, 1.5, 0.995, NA) ## , c(-.4, 1.25, 0.975, NA) , c(-.4, 1.1, 0.975, NA) , c(-.4, 1.025, 0.975, NA) , c(-.4, 1.0125, 0.975, NA) ## ## FIXME , c(-.1, 1.25, 0.95, NA) ## FIXME , c(-.1, 1.25, 0.99, NA) ) st <- system.time( cG.cnst <- lapply(cGs, function(cc) lmrob.control(psi = "ggw", tuning.psi = cc)$tuning.psi) ) cat('Time for constants computation of tuning.psi: ', st,'\n') cGct <- t(sapply(cG.cnst, attr, "constants"))[,-1] colnames(cGct) <- c("a","b","c", "rhoInf") signif(cGct, 4) assert.EQ(sapply(cG.cnst, function(cc) MrhoInf(cc, "ggw")), cGct[,"rhoInf"], tol = 1e-8) ## Do these checks for a *list* of (c.par, psi) combinations: c.psi.list <- list( list(1.345, "Huber"), list(1.8, "Huber"), list(cG, "GGW"), list(c(2,4,8), "Hampel"), list(c(1.5,3.5,8)*0.90, "Hampel"), list(par=c(-.5,1.5,.95,NA), "lqq"), list(bcs=c(1, 1, 1.25), "lqq"), list(1.1, "optimal"), list(0.1, "optimal"), list(2.3, "Welsh") ) for(c.psi in c.psi.list) { tPar <- c.psi[[1]]; psi <- c.psi[[2]] stopifnot(is.numeric(tPar), is.character(psi)) cat("Psi function ", psi,"; tuning par. c[]= (", paste(formatC(tPar, width=1), collapse=", "),")\n") for(FUN in list(Mpsi, Mchi, Mwgt)) stopifnot(identical(d0, FUN(d0, tPar, psi=psi)), identical(NN, FUN(NN, tPar, psi=psi))) stopifnot(identical(c(0,1,0), Mwgt(IoI, tPar,psi=psi))) if(isPsi.redesc(psi)) stopifnot(identical(c(0,0,0), Mpsi(IoI, tPar,psi=psi)), identical(c(1,0,1), Mchi(IoI, tPar,psi=psi))) else if(psi == "Huber") { stopifnot(identical(c(-tPar,0,tPar), Mpsi(IoI, tPar,psi=psi)), identical(c( Inf,0, Inf), Mchi(IoI, tPar,psi=psi))) } cat("chkPsi..(): ") isHH <- psi %in% c("Huber", "Hampel") # not differentiable tol <- switch(tolower(psi), "huber"=, "hampel"= c(.001, 1.0), "optimal" = .008, "ggw" = c(5e-5, 5e-3, 1e-12), "lqq" = c(1e-5, 5e-5, 1e-5, .08)) # .08 needed for bcs=c(1, 1, 1.25) if(is.null(tol)) tol <- 1e-4 # default otherwise cc <- chkPsi..(c(-5, 10), psi=psi, par=tPar, doD2 = !isHH, tol=tol) ## -------- cc. <- cc[!is.na(cc)] if(is.logical(cc) && all(cc.)) cat(" [Ok]\n") else { cat(" not all Ok:\n") print(cc.[cc. != "TRUE"]) } cat("------------------------\n\n") } ## Nice plots -- and check derivatives ---- head(x. <- seq(-5, 10, length=1501)) ## [separate lines, for interactive "play": ] stopifnot(chkPsiDeriv(p.psiFun(x., "LQQ", par=c(-.5,1.5,.95,NA)))) stopifnot(chkPsiDeriv(p.psiFun(x., "GGW", par= cG))) stopifnot(chkPsiDeriv(p.psiFun(x., "optimal", par=2))) stopifnot(chkPsiDeriv(p.psiFun(x., "Hampel", par = ## Default, but rounded: round(c(1.5, 3.5, 8) * 0.9016085, 1)), tol = 1e-3)) stopifnot(chkPsiDeriv(p.psiFun(x., "biweight", par = 4))) stopifnot(chkPsiDeriv(p.psiFun(x., "Welsh", par = 1.5))) stopifnot(chkPsiDeriv(p.psiFun(x., "huber", par = 1.5), tol = c(1e-10, 5e-3))) ## "huber"-rho via Mpsi(*, deriv=-1) was badly wrong till 2018-06 ## The same 6, all in one plot: op <- par(mfrow=c(3,2), mgp = c(1.5, .6, 0), mar = .1+c(3,3,2,.5)) p.psiFun2(x., "LQQ", par=c(-.5,1.5,.95,NA)) p.psiFun2(x., "GGW", par= cG) p.psiFun2(x., "optimal", par=1.3) p.psiFun2(x., "Hampel", par = round(c(1.5, 3.5, 8) * 0.9016085, 1)) p.psiFun2(x., "biweight", par = 4) p.psiFun2(x., "Welsh", par = 1.5) par(op) ### (2) Test them as arguments of lmrob() or lmrob.control(): ----- data(aircraft) set.seed(1) summary(mp0 <- lmrob(Y ~ ., data = aircraft, psi = 'bisquare', method = 'SMDM')) set.seed(2) summary(mp1 <- update(mp0, psi = 'optimal')) set.seed(3) summary(mp2 <- update(mp0, psi = 'ggw')) set.seed(4) summary(mp3 <- update(mp0, psi = 'welsh')) set.seed(5) summary(mp4 <- update(mp0, psi = 'ggw', tuning.psi = c(-.5, 1.5, 0.85, NA), tuning.chi = c(-0.5, 1.5, NA, 0.5))) set.seed(6) summary(mp5 <- update(mp0, psi = 'ggw', tuning.psi = c(-0.5, 1.0, 0.95, NA), tuning.chi = c(-0.5, 1.0, NA, 0.5))) set.seed(7) summary(mp6 <- update(mp0, psi = 'hampel')) set.seed(8) ctr7 <- lmrob.control(psi = 'ggw', tuning.psi = c(-0.3, 1.4, 0.95, NA), tuning.chi = c(-0.3, 1.4, NA, 0.5)) ctr7$tuning.psi ## -> "constants" ctr7$tuning.chi summary(mp7 <-lmrob(Y ~ ., data = aircraft, control = ctr7)) # *not* converging in k.max=200 set.seed(9) summary(mp8 <- update(mp0, psi = 'lqq')) set.seed(10) ## c(.) drops attributes : ctr9 <- lmrob.control(psi = 'lqq', tuning.psi = c(ctr7$tuning.psi), tuning.chi = c(ctr7$tuning.chi)) ctr9$tuning.psi ctr9$tuning.chi ## Confirm these constants above (against the ones we got earlier) ## by recomputing them using higher accuracy : (tpsi. <- do.call(.psi.lqq.findc, c(ctr9$tuning.psi, list(rel.tol=1e-11, tol=1e-8)))) (tchi. <- do.call(.psi.lqq.findc, c(ctr9$tuning.chi, list(rel.tol=1e-11, tol=1e-8)))) (tol4 <- .Machine$double.eps^.25) Rver <- getRversion() integr.bug <- "2.12.0" <= Rver && Rver <= "3.0.1" integr.bug if(integr.bug) tol4 <- 8*tol4 assert.EQ(attr(ctr9$tuning.psi, "constants"), tpsi., tol=tol4, giveRE=TRUE) assert.EQ(attr(ctr9$tuning.chi, "constants"), tchi., tol=tol4, giveRE=TRUE) summary(mp9 <- lmrob(Y ~ ., data = aircraft, control = ctr9)) cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons''