plot.logit.spike.residuals {BoomSpikeSlab} | R Documentation |

##
Residual plot for `logit.spike`

objects.

### Description

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

### Usage

PlotLogitSpikeResiduals(model, ...)
PlotProbitSpikeResiduals(model, ...)

### Arguments

### 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

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)

[Package

*BoomSpikeSlab* version 1.2.4

Index]