SCGLR (version 1.1)

plot.SCGLR: SCGLR generic plot

Description

SCGLR generic plot

Usage

## S3 method for class 'SCGLR':
plot(x, ..., style = "simple",
    threshold = 0.8, plan = c(1, 2), factor = NULL,
    predictors = NULL, covariates = NULL,
    label.offset = 0.01, label.auto = T, label.size = 1,
    expand = 1)

Arguments

x

an object from SCGLR class

...

unused

style

describes which plot will be drawn. Style "simple" : correlation plot, "covariates" (to add co-variates arrows), "circle" (to add the unit circle), "observations" (to add observations), "threshold" (to select co-variates whose sum of square correl

threshold

a numeric value of the sum of square correlations that, variables to be plotted must exceed

plan

a size-2 vector (or comma separated string) indicating which components are plotted (eg: c(1,2) or "1,2")

factor

factor to show (default to first one)

predictors

a vector of character to select the linear predictors displayed

covariates

a vector of character to select the covariates displayed

label.offset

offset by which labels should be moved from tip of arrows

label.auto

whether or not the labels should be rotated according to vector angle

label.size

relative size for labels (fine tuning)

expand

expand factor for windows size, for example to make room for clipped labels

Value

• plot

Examples

library(SCGLR)

# load sample data
data(genus)

# get variable names from dataset
n <- names(genus)
ny <- n[grep("^gen",n)]    # Y <- names that begins with "gen"
nx <- n[-grep("^gen",n)]   # X <- remaining names

# remove "geology" and "surface" from nx
# as surface is offset and we want to use geology as additional covariate
nx <-nx[!nx%in%c("geology","surface")]

# build multivariate formula
# we also add "lat*lon" as computed covariate
form <- multivariateFormula(ny,c(nx,"I(lat*lon)"),c("geology"))

# define family
fam <- rep("poisson",length(ny))

genus.scglr <- scglr(formula=form,data = genus,family=fam, K=4,
 offset=genus$surface)

summary(genus.scglr)

barplot(genus.scglr)

plot(genus.scglr)

plot(genus.scglr,style="circle,cov,predictors,fact")

pairs(genus.scglr)