sparge.modsel: Coeficients distribution [sparge] plot of models selected...

In mmodely: Modeling Multivariate Origins Determinants - Evolutionary Lineages in Ecology

Coeficients distribution [sparge] plot of models selected from each subset

Description

Plot the raw distribution of points corresponding to the coefficients harvested from the best model of each subset of the dataset.

Usage

sparge.modsel(PC, jit.f=1, R2x=3, nx=2, n.max=max(unlist(PC$n)), zeroline=TRUE,
                  add=FALSE, pd=0, pvs=names(PC$coefs), pvlabs=NULL, 
                  xlim=range(unlist(PC$coefs)),
                  MA = NULL, ap=8, ac = 1, ax = nx, ...)

Arguments

PC	a list of vectors of pooled coefficients (or scores) harvested from the 'best' selected modeling runs (out put from 'get.pgls.coefs')
jit.f	factor for random jittering (see 'jitter()'
R2x	the line width expansion factor according to R^2 value
nx	the point size expansion factor according to sample size of model
n.max	the maximum sample size used in all models
zeroline	should we add an abline at x=0?
add	should we add to the existing plot?
pd	'position dodge' moves all y axis plotting positions up or down by this provided value (useful for adding multiple distributions for the same param)
pvs	the predictor variable vector for ordering the y-axis labels
pvlabs	the predictor variable labels for labeling the plot (defaults to pvs)
xlim	x axis plot limits
MA	matrix of model averages (defaults to NULL)
ap	coded numeric point character symbol used for model averaged parameter position
ac	color symbol used for model averaged parameters plot character
ax	expansion factor to expant model average parameter plot character (defaults to nx)
...	other parameters passed on to plot

Value

a 'sparge' [sprinkle/smear] plot of coefficent distributions

See Also

See also 'boxplot' and 'stripchart' in package 'graphics' as well as 'violin', 'bean', 'ridgelines', and 'raincloud' plots.

Examples

data.path <- system.file("extdata","primate-example.data.csv", package="mmodely")
data <- read.csv(data.path, row.names=1)
pvs <- names(data[3:5])
data$gn_sp <- rownames(data)

tree.path <- system.file("extdata","primate-springer.2012.tre", package="mmodely")
phyl <- ape::read.tree(tree.path)[[5]]

mods <- get.model.combos(predictor.vars=pvs, outcome.var='OC', min.q=2)

PGLSi <- pgls.iter(models=mods, phylo=phyl, df=data, k=1,l=1,d=1) 

coefs.objs <- get.pgls.coefs(PGLSi$fits, est='Estimate')

sparge.modsel(coefs.objs)

mmodely documentation built on May 31, 2023, 6:47 p.m.