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pffr.check

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.
refund

Regression with Functional Data

v0.1-23
GPL (>= 2)
Authors
Jeff Goldsmith [aut], Fabian Scheipl [aut], Lei Huang [aut], Julia Wrobel [aut, cre], Chongzhi Di [aut], Jonathan Gellar [aut], Jaroslaw Harezlak [aut], Mathew W. McLean [aut], Bruce Swihart [aut], Luo Xiao [aut], Ciprian Crainiceanu [aut], Philip T. Reiss [aut], Yakuan Chen [ctb], Sonja Greven [ctb], Lan Huo [ctb], Madan Gopal Kundu [ctb], So Young Park [ctb], David L. Miller [ctb], Ana-Maria Staicu [ctb]
Initial release
2020-12-03

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