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# Scatterplot Smoothers (J. Fox and S. Weisberg)
# Sept 17, 2012 moved from scatterplot.R to scatterplotSmoothers.R
# June 18, 2014 Fixed bug in gamLine so the smoother.arg link="linkname" works; thanks to Hani Christoph
# 2014-08-19: Make sure that Matrix and MatrixModels packages are available to quantregLine().
# Can't substitute requireNamespace() for require() for gam and quantreg packages. John
# 2014-11-21: Added 'offset' argument with default 0: offset= sigmaHat(model) for use with
# marginal model plots. Fixed spread smooths as well
# 2015-01-27: gam() and s() now imported from mgcv rqss(), qss(), and fitted.rqss() from quantreg. John
# 2016-11-19: Added argument in smoother.args called 'evaluation'. The smoother will be evaluated
# at evaluation equally spaced points in the range of the horizontal axis, with a default of 50.
# 2017-02-16: explicitly copy mgcv::gam() and mgcv::s(), quantreg::qss() and quantreg::rqss(). John
# 2017-04-17: fixed passing of arguments and use of default.arg. Changed default lwd and lty's
# and names of args see scatterplot.Rd details
# 2017-05-15: fixed spread=TRUE when log="xy". in quantregLine, changed IQR(x) to IQR(x, na.rm=TRUE)
# 2017-06-29: Added defaults for col, log.x, and log.y arguments, and an empty smoother.args.
# 2017-06-30: Changed default line widths and types for smoothers to make them more visible.
# 2017-10-27: Change default lty.smooth to 1 as advertized in docs.
# 2017-11-30: substitute carPalette() for palette(). J. Fox
# 2018-06-25: The argument 'spread' has an alias 'var', with 'var' having precedence. S. Weisberg
# Similarly, col.var, lty.var, lwd.var override col.spread, lty.spread, lwd.spread
# 2018-08-23: gamLine tried to graph in linear predictor scale, not the response scale for glms.
# 2020-09-23: fixed quantregLine() to work with development version 5.69 of the quantreg package. John
# 2020-10-20: added style, alpha, border, and vertical smoother.args and shaded envelope. John
default.arg <- function(args.list, arg, default){
if (is.null(args.list[[arg]])) default else args.list[[arg]]
}
loessLine <- function(x, y, col=carPalette()[1], log.x=FALSE, log.y=FALSE,
var=FALSE, spread=var, smoother.args=NULL,
draw=TRUE, offset=0) {
lty.smooth <- default.arg(smoother.args, "lty.smooth", 1)
lwd.smooth <- default.arg(smoother.args, "lwd.smooth", 2)
col.smooth <- default.arg(smoother.args, "col.smooth", col)
lty.spread <- default.arg(smoother.args, "lty.spread", 4)
lwd.spread <- default.arg(smoother.args, "lwd.spread", 2)
col.spread <- default.arg(smoother.args, "col.spread", col)
# arg '*.spread' and '*.var' are aliased. Use the latter if present
lty.spread <- default.arg(smoother.args, "lty.var", lty.spread)
lwd.spread <- default.arg(smoother.args, "lwd.var", lwd.spread)
col.spread <- default.arg(smoother.args, "col.var", col.spread)
span <- default.arg(smoother.args, "span", 2/3)
family <- default.arg(smoother.args, "family", "symmetric")
degree <- default.arg(smoother.args, "degree", 1)
iterations <- default.arg(smoother.args, "iterations", 4)
evaluation <- default.arg(smoother.args, "evaluation", 50)
style <- match.arg(default.arg(smoother.args, "style", "filled"),
c("filled", "lines", "none"))
if (style == "none") spread <- FALSE
alpha <- default.arg(smoother.args, "alpha", 0.15)
border <- default.arg(smoother.args, "border", TRUE)
vertical <- default.arg(smoother.args, "vertical", TRUE)
if (log.x){ x <- log(x) }
if (log.y){ y <- log(y) }
valid <- complete.cases(x, y)
x <- x[valid]
y <- y[valid]
ord <- order(x)
x <- x[ord]
y <- y[ord]
x.eval <- seq(min(x), max(x), length=evaluation)
warn <- options(warn=-1)
on.exit(options(warn))
# mean smooth
fit <- try(loess(y ~ x, span=span, family=family, degree=degree,
control=loess.control(iterations=iterations)), silent=TRUE)
if (class(fit)[1] != "try-error"){
y.eval <- predict(fit, newdata=data.frame(x=x.eval))
if(draw) {
lines(if(log.x) exp(x.eval) else x.eval,
if(log.y) exp(y.eval) else y.eval,
lwd=lwd.smooth, col=col.smooth, lty=lty.smooth)
}
out <- list(x=if(log.x) exp(x.eval) else x.eval,
y=if(log.y) exp(y.eval) else y.eval)
}
else{ options(warn)
warning("could not fit smooth")
return()}
# spread smooth, if requested
if(spread) {
res <- residuals(fit)
pos <- res > 0
pos.fit <- try(loess(I(res^2) ~ x, span=span, degree=0, family=family, subset=pos,
control=loess.control(iterations=1)),
silent=TRUE)
neg.fit <- try(loess(I(res^2) ~ x, span=span, degree=0, family=family, subset=!pos,
control=loess.control(iterations=1)),
silent=TRUE)
if(class(pos.fit)[1] != "try-error"){
y.pos <- y.eval + sqrt(offset^2 + predict(pos.fit, newdata=data.frame(x=x.eval)))
y.pos <- if (log.y) exp(y.pos) else y.pos
if(draw && style == "lines") {
lines(if(log.x) exp(x.eval) else x.eval, y.pos,
lwd=lwd.spread, lty=lty.spread, col=col.spread)
} else {
out$x.pos <- if(log.x) exp(x.eval) else x.eval
out$y.pos <- y.pos
}
}
else{
options(warn)
warning("could not fit positive part of the spread")
}
if(class(neg.fit)[1] != "try-error"){
y.neg <- y.eval - sqrt(offset^2 + predict(neg.fit, newdata=data.frame(x=x.eval)))
y.neg <- if (log.y) exp(y.neg) else y.neg
if(draw && style == "lines") {
lines(if(log.x) exp(x.eval) else x.eval, y.neg,
lwd=lwd.spread, lty=lty.spread, col=col.spread)
} else {
out$x.neg <- if(log.x) exp(x.eval) else x.eval
out$y.neg <- y.neg
}
} else {
options(warn)
warning("could not fit negative part of the spread")
}
if (draw && style == "filled"){
if (vertical){
with(out, {
good <- complete.cases(x.neg, x.pos, y.neg, y.pos)
envelope(x.neg[good], x.pos[good], y.neg[good], y.pos[good],
col=col.spread, alpha=alpha, border=border)
})
} else {
with(out, {
good.neg <- !is.na(y.neg)
good.pos <- !is.na(y.pos)
envelope(x.neg[good.neg], x.pos[good.pos], y.neg[good.neg], y.pos[good.pos],
col=col.spread, alpha=alpha, border=border)
})
}
}
}
if(!draw) return(out)
}
gamLine <- function(x, y, col=carPalette()[1], log.x=FALSE, log.y=FALSE,
var=FALSE, spread=var, smoother.args=NULL, draw=TRUE, offset=0) {
gam <- mgcv::gam
s <- mgcv::s
lty.smooth <- default.arg(smoother.args, "lty.smooth", 1)
lwd.smooth <- default.arg(smoother.args, "lwd.smooth", 2)
col.smooth <- default.arg(smoother.args, "col.smooth", col)
lty.spread <- default.arg(smoother.args, "lty.spread", 4)
lwd.spread <- default.arg(smoother.args, "lwd.spread", 2)
col.spread <- default.arg(smoother.args, "col.spread", col)
# arg '*.spread' and '*.var' are aliased. Use the latter if present
lty.spread <- default.arg(smoother.args, "lty.var", lty.spread)
lwd.spread <- default.arg(smoother.args, "lwd.var", lwd.spread)
col.spread <- default.arg(smoother.args, "col.var", col.spread)
fam <- default.arg(smoother.args, "family", gaussian)
link <- default.arg(smoother.args, "link", NULL)
evaluation <- default.arg(smoother.args, "evaluation", 50)
style <- match.arg(default.arg(smoother.args, "style", "filled"),
c("filled", "lines", "none"))
if (style == "none") spread <- FALSE
alpha <- default.arg(smoother.args, "alpha", 0.15)
border <- default.arg(smoother.args, "border", TRUE)
vertical <- default.arg(smoother.args, "vertical", TRUE)
fam <- if(is.character(fam)) eval(parse(text=fam)) else fam
link <- if(is.character(link)) make.link(link) else link
k <- default.arg(smoother.args, "k", -1)
bs <- default.arg(smoother.args, "bs", "tp")
if (is.character(family)) family <- eval(parse(text=family))
weights <- default.arg(smoother.args, "weights", NULL)
spread <- spread && identical(fam, gaussian) && is.null(link)
if (log.x) x <- log(x)
if (log.y) y <- log(y)
valid <- complete.cases(x, y)
x <- x[valid]
y <- y[valid]
ord <- order(x)
x <- x[ord]
y <- y[ord]
x.eval <- seq(min(x), max(x), length=evaluation)
w <-if (is.null(weights)) rep(1, length(y))
else weights[valid][ord]
warn <- options(warn=-1)
on.exit(options(warn))
fam1 <- if(is.null(link)) fam else fam(link)
fit <- try(gam(y ~ s(x, k=k, bs=bs), weights=w, family=fam1))
if (class(fit)[1] != "try-error"){
y.eval <- predict(fit, newdata=data.frame(x=x.eval), type="response")
if(draw)lines(if(log.x) exp(x.eval) else x.eval,
if(log.y) exp(y.eval) else y.eval,
lwd=lwd.smooth, col=col.smooth, lty=lty.smooth)
out <- list(x=if(log.x) exp(x.eval) else x.eval,
y=if(log.y) exp(y.eval) else y.eval)
}
else{ options(warn)
warning("could not fit smooth")
return()}
if(spread) {
res <- residuals(fit)
pos <- res > 0
pos.fit <- try(gam(I(res^2) ~ s(x, k=k, bs=bs), subset=pos), silent=TRUE)
neg.fit <- try(gam(I(res^2) ~ s(x, k=k, bs=bs), subset=!pos), silent=TRUE)
if(class(pos.fit)[1] != "try-error"){
y.pos <- y.eval + sqrt(offset^2 +
predict(pos.fit, newdata=data.frame(x=x.eval), type="response"))
if(draw && style == "lines") {
lines(if(log.x) exp(x.eval) else x.eval,
if(log.y) exp(y.pos) else y.pos,
lwd=lwd.spread, lty=lty.spread, col=col.spread)
} else {
out$x.pos <- if(log.x) exp(x.eval) else x.eval
out$y.pos <- if(log.y) exp(y.pos) else y.pos
}
}
else{ options(warn)
warning("could not fit positive part of the spread")
}
if(class(neg.fit)[1] != "try-error"){
y.neg <- y.eval - sqrt(offset^2 +
predict(neg.fit, newdata=data.frame(x=x.eval), type="response"))
if(draw && style == "lines") {
lines(if(log.x) exp(x.eval) else x.eval,
if(log.y) exp(y.neg) else y.neg,
lwd=lwd.spread, lty=lty.spread, col=col.spread)
} else {
out$x.neg <- if(log.x) exp(x.eval) else x.eval
out$y.neg <- if(log.y) exp(y.neg) else y.neg
}
} else {
options(warn)
warning("could not fit negative part of the spread")
}
if (draw && style == "filled"){
if (vertical){
with(out, {
good <- complete.cases(x.neg, x.pos, y.neg, y.pos)
envelope(x.neg[good], x.pos[good], y.neg[good], y.pos[good],
col=col.spread, alpha=alpha, border=border)
})
} else {
with(out, {
good.neg <- !is.na(y.neg)
good.pos <- !is.na(y.pos)
envelope(x.neg[good.neg], x.pos[good.pos], y.neg[good.neg], y.pos[good.pos],
col=col.spread, alpha=alpha, border=border)
})
}
}
}
if(!draw) return(out)
}
quantregLine <- function(x, y, col=carPalette()[1], log.x=FALSE, log.y=FALSE,
var=FALSE, spread=var, smoother.args=NULL, draw=TRUE, offset=0) {
if (!package.installed("Matrix")) stop("the Matrix package is missing")
if (!package.installed("MatrixModels")) stop("the MatrixModels package is missing")
if (!package.installed("SparseM")) stop("the SparseM package is missing")
qss <- quantreg::qss
rqss <- quantreg::rqss
lty.smooth <- default.arg(smoother.args, "lty.smooth", 1)
lwd.smooth <- default.arg(smoother.args, "lwd.smooth", 2)
col.smooth <- default.arg(smoother.args, "col.smooth", col)
lty.spread <- default.arg(smoother.args, "lty.spread", 4)
lwd.spread <- default.arg(smoother.args, "lwd.spread", 2)
col.spread <- default.arg(smoother.args, "col.spread", col)
# arg '*.spread' and '*.var' are aliased. Use the latter if present
lty.spread <- default.arg(smoother.args, "lty.var", lty.spread)
lwd.spread <- default.arg(smoother.args, "lwd.var", lwd.spread)
col.spread <- default.arg(smoother.args, "col.var", col.spread)
style <- match.arg(default.arg(smoother.args, "style", "filled"),
c("filled", "lines", "none"))
if (style == "none") spread <- FALSE
alpha <- default.arg(smoother.args, "alpha", 0.15)
border <- default.arg(smoother.args, "border", TRUE)
vertical <- default.arg(smoother.args, "vertical", TRUE)
evaluation <- default.arg(smoother.args, "evaluation", 50)
if (log.x) x <- log(x)
if (log.y) y <- log(y)
lambda <- default.arg(smoother.args, "lambda", IQR(x, na.rm=TRUE))
valid <- complete.cases(x, y)
x <- x[valid]
y <- y[valid]
ord <- order(x)
x <- x[ord]
y <- y[ord]
x.eval <- seq(min(x), max(x), length=evaluation)
Data <- data.frame(x, y)
if (!spread){
fit <- rqss(y ~ qss(x, lambda=lambda), data=Data)
y.eval <- predict(fit, newdata=data.frame(x=x.eval))
y.eval <- if(log.y) exp(y.eval) else y.eval
if(draw)lines(if(log.x) exp(x.eval) else x.eval, y.eval, lwd=lwd.smooth,
col=col, lty=lty.smooth) else
out <- list(x=if(log.x) exp(x.eval) else x.eval, y=y.eval)
}
else{
fit <- rqss(y ~ qss(x, lambda=lambda), data=Data)
q1fit <- rqss(y ~ qss(x, lambda=lambda), tau=0.25, data=Data)
q3fit <- rqss(y ~ qss(x, lambda=lambda), tau=0.75, data=Data)
y.eval <- predict(fit, newdata=data.frame(x=x.eval))
y.eval.q1 <- predict(q1fit, newdata=data.frame(x=x.eval))
y.eval.q3 <- predict(q3fit, newdata=data.frame(x=x.eval))
y.eval <- if(log.y) exp(y.eval) else y.eval
y.eval.q1 <- if(log.y) exp(y.eval.q1) else y.eval.q1
y.eval.q3 <- if(log.y) exp(y.eval.q3) else y.eval.q3
# adjust for offset
y.eval.q1 <- y.eval - sqrt( (y.eval-y.eval.q1)^2 + offset^2)
y.eval.q3 <- y.eval + sqrt( (y.eval-y.eval.q3)^2 + offset^2)
if (draw) {
lines(if(log.x) exp(x.eval) else x.eval, y.eval,
lwd=lwd.smooth, col=col.smooth, lty=lty.smooth)
}
if(draw && style == "lines") {
lines(if(log.x) exp(x.eval) else x.eval, y.eval.q1,
lwd=lwd.spread, lty=lty.spread, col=col.spread)
lines(if(log.x) exp(x.eval) else x.eval, y.eval.q3,
lwd=lwd.spread, lty=lty.spread, col=col.spread)
} else {
x.eval <- if(log.x) exp(x.eval) else x.eval
out <- list(x=x.eval, y=y.eval)
out$x.neg <- x.eval
out$y.neg <- y.eval.q1
out$x.pos <- x.eval
out$y.pos <- y.eval.q3
}
if (draw && style == "filled"){
if (vertical){
with(out, {
good <- complete.cases(x.neg, x.pos, y.neg, y.pos)
envelope(x.neg[good], x.pos[good], y.neg[good], y.pos[good],
col=col.spread, alpha=alpha, border=border)
})
} else {
with(out, {
good.neg <- !is.na(y.neg)
good.pos <- !is.na(y.pos)
envelope(x.neg[good.neg], x.pos[good.pos], y.neg[good.neg], y.pos[good.pos],
col=col.spread, alpha=alpha, border=border)
})
}
}
}
if(!draw) return(out)
}
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