This is simply a wrapper for
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", ... )
If you want old fashioned plots, exactly as in Wood, 2006, set to
type of residuals, see
residuals.gam, used in
Above this k testing uses a random sub-sample of data.
how many re-shuffles to do to get p-value for k testing.
extra graphics parameters to pass to plotting functions.