pffr.check: Some diagnostics for a fitted pffr model
In refund: Regression with Functional Data

pffr.check

R Documentation

Some diagnostics for a fitted pffr model

Description

This is simply a wrapper for gam.check().

Usage

pffr.check(
  b,
  old.style = FALSE,
  type = c("deviance", "pearson", "response"),
  k.sample = 5000,
  k.rep = 200,
  rep = 0,
  level = 0.9,
  rl.col = 2,
  rep.col = "gray80",
  ...
)

Arguments

`b`	a fitted `pffr`-object
`old.style`	If you want old fashioned plots, exactly as in Wood, 2006, set to `TRUE`.
`type`	type of residuals, see `residuals.gam`, used in all plots.
`k.sample`	Above this k testing uses a random sub-sample of data.
`k.rep`	how many re-shuffles to do to get p-value for k testing.
`rep`	passed to `qq.gam` when `old.style` is `FALSE`.
`level`	passed to `qq.gam` when `old.style` is `FALSE`.
`rl.col`	passed to `qq.gam` when `old.style` is `FALSE`.
`rep.col`	passed to `qq.gam` when `old.style` is `FALSE`.
`...`	extra graphics parameters to pass to plotting functions.