zoom.qqGam: Efficiently zooming on GAM QQ-plots

In mgcViz: Visualisations for Generalized Additive Models

Efficiently zooming on GAM QQ-plots

Description

This function allows to zoom into a QQ-plot produced by qq.gamViz, in a computationally efficient manner.

Usage

## S3 method for class 'qqGam'
zoom(
  o,
  xlim = NULL,
  ylim = NULL,
  discrete = NULL,
  ngr = 1000,
  adGrid = TRUE,
  CI = FALSE,
  worm = FALSE,
  showReps = FALSE,
  a.qqpoi = list(),
  a.ablin = list(),
  a.cipoly = list(),
  a.replin = list(),
  ...
)

Arguments

o	the output of mgcViz::qq.gamViz.
xlim	if supplied then this pair of numbers are used as the x limits for the plot.
ylim	if supplied then this pair of numbers are used as the y limits for the plot.
discrete	if TRUE the QQ-plot is discretized into ngr bins before plotting, in order to save plotting time (when the number of observations is large). If left to NULL, the discretization is used if there are more than 10^4 observations.
ngr	number of bins to be used in the discretization.
adGrid	if TRUE the discretization grid is computed using the QQ-points falling within xlim. If FALSE, zoom.qqGam will compute ngr values using all the QQ-points used in the original qq.gamViz call (but only those falling within xlim and ylim will be plotted).
CI	if TRUE confidence intervals are plotted.
worm	if TRUE a worm-plot (a de-trended QQ-plot) is plotted, rather than a QQ-plot.
showReps	if TRUE all the QQ-lines corresponding to the simulated (model-based) QQ-plots.
a.qqpoi	list of arguments to be passed to ggplot2::geom_point, which plots the main QQ-plot.
a.ablin	list of arguments to be passed to ggplot2::geom_abline, which adds the reference line.
a.cipoly	list of arguments to be passed to ggplot2::geom_polygon, which add the confidence intervals.
a.replin	list of arguments to be passed to ggplot2::geom_line, which adds a line for each simulated QQ-plot.
...	currently unused.

Examples

library(mgcViz);
set.seed(0)
n.samp <- 500
dat <- gamSim(1,n=n.samp,dist="binary",scale=.33)
p <- binomial()$linkinv(dat$f) ## binomial p
n <- sample(c(1,3),n.samp,replace=TRUE) ## binomial n
dat$y <- rbinom(n,n,p)
dat$n <- n
lr.fit <- bam(y/n ~ s(x0) + s(x1) + s(x2) + s(x3)
              , family = binomial, data = dat,
              weights = n, method = "REML")
lr.fit <- getViz(lr.fit)

set.seed(414)
o <- qq(lr.fit, rep = 50, method = "simul1", CI = "normal")
o # This is the whole qqplot

# We can zoom in along x at little extra costs (most computation already done by qq.gamViz)
zoom(o, xlim = c(0, 1), showReps = TRUE, 
     a.replin = list(alpha = 0.1), a.qqpoi =  list(shape = 19))

mgcViz documentation built on Oct. 6, 2023, 5:09 p.m.