Nothing
regPlot <-
function(out, type, d.ancova, digits_d=NULL, pred.intervals=TRUE,
res_sort=c("cooks","rstudent","dffits","off"),
n_res_rows=NULL, cooks_cut=1, scatter_coef=NULL,
pdf=FALSE, width=5, height=5, manage.gr=FALSE, ...) {
if (options("device") != "RStudioGD" && is.null(options()$knitr.in.progress))
.graphwin(1)
# need: out$residuals
if (type == 2) .reg3dnResidual(out, pdf, width, height, manage.gr)
# need: out$fitted.values, out$residuals
if (type == 3) .reg3resfitResidual(out, out$cooks.distance, cooks_cut,
pdf=FALSE, width=5, height=5, manage.gr=FALSE)
# need: out$model (the data)
if (type == 1) {
#nm <- all.vars(out$terms) # names of vars in the model
nm <- all.vars(out$formula)
n.vars <- length(nm)
n.pred <- n.vars - 1
in.data.frame <- TRUE
for (i in 1:n.vars) {
if (!(nm[i] %in% names(out$model))) {
cat("\n\n\n>>> Note: ", nm[i], "is not in the data frame.\n")
in.data.frame <- FALSE
}
}
# check for all numeric vars in.data.frame <- TRUE
numeric.all <- TRUE
for (i in 1:n.vars) {
if (in.data.frame &&
!is.numeric(out$model[1,which(names(out$model) == nm[i])])) {
cat("\n\n\n>>> Note: ", nm[i], "is not a numeric variable.\n")
numeric.all <- FALSE
}
}
if (pred.intervals) {
data <- out$model
if (n.pred == 1) {
o <- order(data[,nm[2]], decreasing=FALSE)
data <- data[o,]
}
r2.out <- lm(out$formula, data=data)
c.int <- data.frame(predict(r2.out, interval="confidence"),
stringsAsFactors=TRUE)
p.int <- data.frame(suppressWarnings(predict(r2.out,
interval="prediction")), stringsAsFactors=TRUE)
}
else {
c.int <- NULL
p.int <- NULL
n_pred_rows <- 0
}
if (!is.null(scatter_coef))
s.c <- scatter_coef
else
s.c <- TRUE
if (is.null(d.ancova))
.reg5Plot(out, n_res_rows=NULL, n_pred_rows=NULL,
scatter_coef=s.c, X1_new=NULL,
in.data.frame, c.int, p.int,
digits_d=getOption("digits_d"), n_cat=getOption("n_cat"),
pdf=FALSE, width=5, height=5, manage.gr=FALSE, ...)
else
.reg5ancova(out, d.ancova, digits_d=getOption("digits_d"),
pdf=FALSE, width=5, height=5, manage.gr=FALSE, ...)
} # end type == 1
}
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