gldrmPIT: Confidence intervals for gldrm coefficients
In gldrm: Generalized Linear Density Ratio Models

Description Usage Arguments Details Value Examples

Plots and returns the randomized probability inverse transform of a fitted gldrm.

1 2	gldrmPIT(gldrmFit, nbreaks = 7, cex.main = NULL, cex.lab = NULL, cex.axis = NULL)

`gldrmFit`	A gldrm model fit. Must be an S3 object of class "gldrm", returned from the `gldrm` function. The matrix of semiparametric tilted probabilities must be returned, which is done by fitting gldrm with `gldrmControl = gldrm.control(returnfTiltMatrix = TRUE)`.
`nbreaks`	Number of breaks in the histogram.
`cex.main`	Text size for main titles.
`cex.lab`	Text size for axis labels.
`cex.axis`	Text size for axis numbers.

The probability inverse transform is defined generally as \hat{F}(y|x), which is the fitted conditional cdf of each observation evaluated at the observed response value. In the case of gldrm, the fitted cdf is descrete, so we draw a random value from a uniform distribution on the interval (\hat{F}(y|x), \hat{F}(y-|x)), where y- is the next largest observed support less than y (or -Infinity if y is the minimum support value). The output and plots generated by this function will vary slightly each time it is called (unless the random number generator seed is set beforehand).

Randomized robability inverse transform as a vector. Also plots the histogram and uniform QQ plot.

data(iris, package="datasets")

### Fit gldrm and return fTiltMatrix
fit <- gldrm(Sepal.Length ~ Sepal.Width + Petal.Length + Petal.Width + Species,
             data=iris, link="log")
             
# Probability inverse transform plot
gldrmPIT(fit)