gg_hmf: Heatmap Fit Plot using GGplot

In psre: Presenting Statistical Results Effectively

Heatmap Fit Plot using GGplot

Description

Makes a Heatmap Fit plot (Esary and Pierce, 2012) using GGPlot rather than lattice that the heatmapFit package uses.

Usage

gg_hmf(
  observed,
  prob,
  method = c("loess", "gam"),
  span = NULL,
  nbin = 20,
  R = 1000,
  ...
)

Arguments

observed	Vector of observe (0/1) values used in a binary regression model.
prob	Vector of predicted probabilities from the model with observed as the dependent variable.
method	Method for making the line - LOESS or GAM (from the mgcv package.)
span	Optional span parameter to be passed in. If NULL, AICc will be used to find the appropriate span for the loess smooth.
nbin	Number of bins for the histogram.
R	Number of boostrap resamples
...	Currently unimplemented.

Value

Two ggplots - the main heatmap Fit plot and a histogram that can be included as a marginal density.

Examples

data(india)
india$bjp <- ifelse(india$in_prty == 2, 1, 0)
mod1 <- glm(bjp ~  educyrs + anti_immigration, 
            data=india, family=binomial)

gh1 <- gg_hmf(model.response(model.frame(mod1)), 
              fitted(mod1), 
              method="loess")

psre documentation built on Aug. 8, 2022, 5:05 p.m.