plot.logit.spike.residuals: Residual plot for logit.spike objects.

Description

Plots the "deviance residuals" from a logit.spike model.

Usage

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Arguments

model

A model object inheriting from logit.spike or probit.spike.

...

Additional arguments to be passed to plot.

Details

The "deviance residuals" are defined as the signed square root each observation's contribution to log likelihood. The sign of the residual is positive if half or more of the trials associated with an observation are successes. The sign is negative otherwise.

The "contribution to log likelihood" is taken to be the posterior mean of an observations log likelihood contribution, averaged over the life of the MCMC chain.

The deviance residual is plotted against the fitted value, again averaged over the life of the MCMC chain.

The plot also shows the .95 and .99 bounds from the square root of a chi-square(1) random variable. As a rough approximation, about 5% and 1% of the data should lie outside these bounds.

Author(s)

Steven L. Scott

See Also

logit.spike plot.logit.spike

Examples

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simulate.logit.spike <- function(n = 100, p = 10, ngood = 3,
                              niter=1000){
  x <- cbind(1, matrix(rnorm(n * (p-1)), nrow=n))
  beta <- c(rnorm(ngood), rep(0, p - ngood))
  prob <- plogis(x %*% beta)
  y <- runif(n) < prob
  x <- x[,-1]
  draws <- logit.spike(y ~ x, niter=niter)
  plot.ts(draws$beta)
  return(invisible(draws))
}
model <- simulate.logit.spike()
plot(model, "fit")
plot(model, "fit", scale = "probability", number.of.buckets = 15)

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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