gbm.lmplots: Plot linear models for all expvar against the resvar
In SimonDedman/gbm.auto: Automated Boosted Regression Tree Modelling and Mapping Suite

gbm.lmplots

R Documentation

Plot linear models for all expvar against the resvar

Description

Loops the lmplot function, shows linear model plots for all expvar against the resvar. Good practice to do this before running gbm.auto so you have a sense of the basic relationship of the variables.

Usage

gbm.lmplots(
  samples = NULL,
  expvar = NULL,
  resvar = NULL,
  expvarnames = NULL,
  resvarname = NULL,
  savedir = NULL,
  plotname = NULL,
  pngtype = c("cairo-png", "quartz", "Xlib"),
  r2line = TRUE,
  pointtext = FALSE,
  pointlabs = resvar,
  pointcol = "black",
  ...
)

Arguments

`samples`	Explanatory and response variables to predict from. Keep col names short (~17 characters max), no odd characters, spaces, starting numerals or terminal periods. Spaces may be converted to periods in directory names, underscores won't. Can be a subset of a large dataset.
`expvar`	Vector of names or column numbers of explanatory variables in 'samples': c(1,3,6) or c("Temp","Sal"). No default.
`resvar`	Name or column number(s) of response variable in samples: 12, c(1,4), "Rockfish". No default. Column name is ideally species name.
`expvarnames`	Vector of names same length as expvar, if you want nicer names.
`resvarname`	Single character object, if you want a nicer resvar name.
`savedir`	Save location, end with "/".
`plotname`	Character vector of plot names else expvarnames else expvar will be used.
`pngtype`	Filetype for png files, alternatively try "quartz" on Mac.
`r2line`	Plot rsquared trendline, default TRUE.
`pointtext`	Label each point? Default FALSE.
`pointlabs`	Point labels, defaults to resvar value.
`pointcol`	Points colour, default "black".
`...`	Allows controlling of text label params e.g. adj cex &.