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## Purpose: residuals method for haplo.glm object
## Author: Jason Sinnwell
## Created: 9/26/2011
residuals.haplo.glm <- function (object, type = c("deviance", "pearson",
"working", "response"), ...)
{
type <- match.arg(type)
## We do not implement predict for haplo.glm, so partial is not allowed
if(type=="partial")
stop("partial residuals not supported for haplo.glm\n")
## Fix elements of haplo.glm object so that it will work
## with residuals.glm function
sindx <- object$haplo.post.info$indx
hpost <- object$haplo.post.info$post
## create collapsed y
mu.eta <- object$family$mu.eta
y <- object$fitted.values +
object$residuals * mu.eta(object$linear.predictors)
object$y <- tapply(object$y, sindx, FUN=function(x) signif(x[1],digits=4))
## collapse mu, and weights, and working residuals
## assign them back to object before calling residuals.glm on it
mu <- tapply(object$fitted.values*hpost, sindx, sum)
wts <- tapply(object$prior.weights, sindx, FUN <- function(x) x[1])
object$fitted.values <- mu
object$residuals <- tapply(object$residuals*object$prior.weights*hpost,
sindx,sum)
object$prior.weights <- wts
res <- residuals.glm(object, type=type)
return(res)
}
## Purpose: method to get fitted.values for haplo.glm object
## Author: Jason Sinnwell
## Created: 10/3/2011
fitted.haplo.glm <- function(object, ...) {
sindx <- object$haplo.post.info$indx
hpost <- object$haplo.post.info$post
fits <- tapply(object$fitted.values*hpost, sindx, sum)
return(fits)
}
## Purpose: method to get var-cov matrix for haplo.glm object
## Author: Jason Sinnwell
## Created: 10/4/2011
vcov.haplo.glm <- function(object, freq=TRUE, ...) {
if(freq) {
return(object$var.mat)
} else {
return(object$var.mat[1:object$rank,1:object$rank])
}
}
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