## ----preliminary, echo=F, message=F------------------------------------------- ## library(plgraphics, lib.loc="/u/stahel/R/regdevelop/pkg/plgraphics.Rcheck") library(relevance) ##, lib.loc="/u/stahel/R/regdevelop/pkg/relevance.Rcheck") ## options(warn=1) ## ----rlvthres----------------------------------------------------------------- getOption("rlv.threshold") ## ----twosamples--------------------------------------------------------------- t.test(sleep[sleep$group == 1, "extra"], sleep[sleep$group == 2, "extra"]) ( r.sleep <- twosamples(sleep[sleep$group == 1, "extra"], sleep[sleep$group == 2, "extra"]) ) ## ----sleep2------------------------------------------------------------------- t.oldopt <- options(show.inference = "classical") r.sleep options(t.oldopt) ## restore the old options ## ----correlation-------------------------------------------------------------- correlation(iris[1:50,1:2], method="spearman") ## ----termtable---------------------------------------------------------------- data(swiss, package="datasets") rr <- lm(Fertility ~ . , data = swiss) rt <- termtable(rr) rt names(rt) ## The result of termtable has 24 columns ## The following statements are commented out to avoid excessive output ## str(rt) ## data.frame(rt) ## or print(rt, show="all") ## This avoids selection and preparation of columns by 'print.inference'. ## ----1 df ## ----inference---------------------------------------------------------------- ( rr <- inference(r.blast) ) ## ----replication-------------------------------------------------------------- data(d.osc15Onesample) to <- structure(d.osc15Onesample[,c("effecto","teststatistico","no")], names=c("effect","teststatistic","n")) tr <- structure(d.osc15Onesample[,c("effectr","teststatisticr","nr")], names=c("effect","teststatistic","n")) ( rr <- replication(to, tr, rlv.threshold=0.1) ) plot(rr) ## ----replication.plgroups----------------------------------------------------- plot(attr(rr, "estimate"), refline=c(0,1), label2=attr(rr, "rplclass"), xlab="relevance") ## ----show--------------------------------------------------------------------- showd(d.blast) ## ----getOption---------------------------------------------------------------- t.opt <- options(show.terms.relevance=c("coef", "dropRls", "dropRls.symbol")) rt ## restore the old options options(t.opt) ## the former options options(relevance.options) ## restore the package's defaults ## ----printlist---------------------------------------------------------------- rpr <- print(termeffects(r.blast), print=FALSE) attr(rpr, "head") <- sub("lm", "Linear Regression", attr(rpr, "head")) rpr ## ----sleep-------------------------------------------------------------------- data(sleep) dd <- subset(sleep, group==2) onesample(60*dd$extra, rlv.threshold=60, standardize=FALSE) ## ----anchoring, fig.height=4, fig.width=9------------------------------------- data(d.everest) rr <- twosamples(log(y)~g, data=d.everest, var.equal=TRUE) print(rr, show="classical") rr pltwosamples(log(y)~g, data=d.everest) ## ----blast, fig.height=3------------------------------------------------------ dd <- d.blast[seq(1,388,3),] dd <- na.omit(dd[dd$location %in% paste("loc",c(1,2,4),sep=""),]) dd$time <- as.numeric(dd$date-min(dd$date))/365 rlm <- lm(log10(tremor)~location+log10(distance)+log10(charge)+time, data=dd, contrasts=list(location="contr.sum")) ( rt <- termtable(rlm) ) plot(rt)