post.check: Diagnostic plots for discrete/continuous response margin

Description Usage Arguments Details Value Author(s) See Also

View source: R/post.check.R

Description

It produces diagnostic plots based on (randomised) quantile residuals.

Usage

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post.check(x, main = "Histogram and Density Estimate of Residuals", 
           main2 = "Histogram and Density Estimate of Residuals",
           xlab = "Quantile Residuals", xlab2 = "Quantile Residuals", 
           intervals = FALSE, n.sim = 100, prob.lev = 0.05, ...)

Arguments

x

A fitted copulaReg/copulaSampleSel object.

main

Title for the plot.

main2

Title for the plot in the second row. This comes into play only when fitting models with two non-binary margins.

xlab

Title for the x axis.

xlab2

Title for the x axis in the second row. As above.

intervals

If TRUE then intervals for the qqplots are produced.

n.sim

Number of replicate datasets used to simulate quantiles of the residual distribution.

prob.lev

Overall probability of the left and right tails of the probabilities' distributions used for interval calculations.

...

Other graphics parameters to pass on to plotting commands.

Details

If the model fits the response well then the plots should look normally distributed. When fitting models with discrete and/or continuous margins, four plots will be produced. In this case, the arguments main2 and xlab2 come into play and allow for different labelling across the plots.

Value

qr

It returns the (randomised) quantile residuals for the continuous or discrete margin when fitting a model that involves a binary response.

qr1

As above but for first equation (this applies when fitting models with continuous/discrete margins).

qr2

As above but for second equation.

Author(s)

Maintainer: Giampiero Marra [email protected]

See Also

copulaReg, copulaSampleSel


JRM documentation built on July 13, 2017, 5:03 p.m.