plregr.control {plgraphics}R Documentation

Further Arguments to plregr

Description

Specify some arguments of minor importance for the function plregr

Usage

plregr.control(x, data = NULL, xvar = TRUE, transformed = FALSE,
  weights = NULL, stdresid = TRUE, mar = NULL,
  glm.restype = "working", condquant = TRUE, smresid = TRUE,
  partial.resid = TRUE, cookdistlines = 1:2,
  leveragelimit = c(0.99, 0.5), condprobRange = NULL,
  refline = TRUE, reflineband = FALSE, testlevel = 0.05,
  smooth = 2, 
  smooth.sim = NULL,
  xlabs = NULL, reslabs = NULL, markextremes = NULL,
  mf = TRUE, mfcol = FALSE, multnrow = 0, multncol = 0, 
  oma = NULL, ...)

Arguments

x

an object (result of a call to a model fitting function such as lm, glm, .... This is the only argument that is needed. All others have useful defaults.

data

see ?plregr

xvar

variables for which residuals shall be plotted. Either a formula like ~ x1 + x2 or a character vector of names. Defaults to all variables (or terms, see transformed) in the model.

transformed

see ?plregr

weights

logical: should residuals be plotted against weights? Used in plresx.

stdresid

logical: should leverages and standardized residuals be calculated? This is avoided for plresx

mar

plot margins

glm.restype

type of residuals to be used for glm models. In addition to those allowed in residuals() for glm objects, type condquant is possible for (ungrouped) binary regression. See ?residuals.regrpolr for an explanation. Warning: type "deviance" will not work with simulated smooths since NAs will emerge.

condquant

logical: should conditional quantiles be shown for censored observations, binary and ordered responses?

smresid

logical: Should residuals from smooth be used for 'tascale' and 'qq' plots?

partial.resid

if TRUE (default), residuals for observations will be displayed.

cookdistlines

levels of Cook distance for which contours are plotted in the leverage plot

leveragelimit

bound for leverages to be used in standardizing residuals and in calculation of standardized residuals from smooth (if smresid is TRUE).

condprobRange

numeric vector of length 2. In the case of residuals of class condquant, quartile bars are only drawn for residuals with probability between condprobRange[1] and condprobRange[1]. Default is c(0.05,0.8) for less than 50 observations, and c(0,0), suppressing the bars, otherwise.

refline

logical: should reference line be shown?

reflineband

logical: should a confidence band be drawn for the component effects?

testlevel

level for statistical tests

smooth

if TRUE (or 1), smooths are added to the plots where appropriate. If ==2, smmooths to positive and negative residuals-from-smooth are also shown.

smooth.sim

number of simulated smooths added to each plot. If NULL (the default) 19 simulated smooths will be generated if possible and sensible (i.e., none if smooth.group is set).

xlabs

labels for x variables. Defaults to vars

reslabs

labels for vertical axes

markextremes

proportion of extreme residuals to be labeled. If all points should be labeled, let markextremes=1.

mf

vector of 2 elements, indicating the number of rows and columns of panels on each plot page. Defaults to c(2,2), except for multivariate models, where it adjusts to the number of target variables. mf=c(1,1) or mf=1 asks for a single frame per page. mf=NA or mf=0 leaves the framing (and oma) unchanged.

mfcol

if TRUE, the panel will be filled columnwise

multnrow, multncol

number of rows and columns of panels on one page, for residuals of multivariate regression only

oma

vector of length 4 giving the number of lines in the outer margin. If it is of length 2, they refer to top an right margins.

...

further arguments in the call, to be ignored by 'plotregr.control'

Value

A list containing all the items needed to specify plotting in plregr and plresx

Note

This function is not explicitly called by the user, but by plregr and plresx. All the arguments specified here can and should be given as arguments to these functions.

Author(s)

Werner A. Stahel, Seminar for Statistics, ETH Zurich

See Also

plregr and plresx

Examples

data(d.blast)
( r.blast <-
  lm(log10(tremor)~location+log10(distance)+log10(charge), data=d.blast) )

plargs <- plregr.control(r.blast, formula = ~.+distance, transformed=TRUE,
smooth.group = location )
showd(plargs$pdata)
names(plargs)


[Package plgraphics version 1.0 Index]