# R/quasiLik.R In MuMIn: Multi-Model Inference

#### Defines functions qic2qlik

```# Code based on 'compar.gee' from package 'ape'
## Comparative Analysis with GEEs
## compar.gee.R (2011-06-14)
## https://svn.mpl.ird.fr/ape/dev/ape/R/compar.gee.R

##=============================================================================
## quasiLik
##=============================================================================

`quasiLik` <- function (object, ...) UseMethod("quasiLik")

.qlik <- function(y, mu, fam) {
ret <- switch(fam,
gaussian = -sum((y - mu)^2)/2,
binomial = sum(y * log(mu/(1 - mu)) + log(1 - mu)),
#binomial.sqvar = sum(((2 * y - 1) * log(mu /(1 - mu))) - (y / mu) - ((1 - y)/(1 - mu))),
poisson = sum(y * log(mu) - mu),
Gamma = -sum(y/mu + log(mu)),
inverse.gaussian = sum(-y/(2 * mu^2) + 1/mu),
cry(, "do not know how to calculate quasi-likelihood for family '%s'",
fam))
ret
}

`print.quasiLik` <- function (x, digits = getOption("digits"), ...) {
cat("'quasi Lik.' ", paste(format(c(x), digits = digits), collapse = ", "),
"\n", sep = "")
invisible(x)
}

`quasiLik.geeglm` <-
`quasiLik.gee` <-
function(object, ...) {
ret <- .qlik(object\$y, object\$fitted.values, family(object)\$family)
attr(ret, "df") <- NA
attr(ret, "nobs") <- length(object\$y)
class(ret) <- "quasiLik"
ret
}

`quasiLik.yagsResult` <- function(object, ...) {
mu <- object@fitted.values
ret <- .qlik(mu + object@residuals, mu, family(object)\$family)
attr(ret, "df") <- NA
attr(ret, "nobs") <- length(mu)
class(ret) <- "quasiLik"
ret
}

`quasiLik.geem` <-
function(object, ...) {
fam <- family(object)
ret <- .qlik(object\$y, fitted(object), if(inherits(fam, "family"))
fam\$family else "custom")
attr(ret, "df") <- NA
attr(ret, "nobs") <- length(object\$y)
class(ret) <- "quasiLik"
ret
}

##=============================================================================
## QIC
##=============================================================================

.qic2 <- function(y, mu, vbeta, mui, vbeta.naiv.i, fam, typeR = FALSE) {
ql <- if(typeR) .qlik(y, mu, fam) else .qlik(y, mui, fam)
# XXX: should be typeR = TRUE for QICu???
n <- length(y)
# yags/yags.cc: p140 of Hardin and Hilbe
if(fam == "gaussian") ql <- (n * log(-2 * ql / n)) / -2
AIinv <- solve(vbeta.naiv.i)
tr <- sum(matmult(AIinv, vbeta, diag.only = TRUE))
## tr <- sum(diag(AIinv %*% vbeta))
px <- length(mu)
## When all modelling specifications in GEE are correct tr = px.
c(2 * (c(QIC = tr, QICu = px) - ql), n = n)
}

`getQIC` <-
function(x, typeR = FALSE) UseMethod("getQIC")

`getQIC.default` <-
function(x, typeR = FALSE) .NotYetImplemented()

`getQIC.coxph` <- function(x, ...) {
warning("QIC for 'coxph' is experimental")
naive.var <- x[[ if (is.null(x\$naive.var)) "var" else "naive.var" ]]
# tr <- sum(diag(solve(naive.var) %*% x\$var))
tr <- sum(matmultdiag(solve(naive.var), x\$var))
ll <- x\$loglik[2L]
px <- x\$n
c(2 * (c(QIC = tr, QICu = px) - ll), n = px)
}

`getQIC.gee` <-
function(x, typeR = FALSE) {
if(x\$model\$corstr != "Independent")
utils::capture.output(suppressMessages(xi <- update(x, corstr = "independence",
silent = TRUE))) else
xi <- x

.qic2(x\$y, x\$fitted.values, x\$robust.variance,
xi\$fitted.values, xi\$naive.variance, family(x)\$family,
typeR = typeR)
}

`getQIC.geeglm` <-
function(x, typeR = FALSE) {
xi <- if(x\$corstr != "independence")
update(x, corstr = "independence") else x
.qic2(x\$y, x\$fitted.values, x\$geese\$vbeta,
xi\$fitted.values, xi\$geese\$vbeta.naiv, family(x)\$family,
typeR = typeR)
}

`getQIC.yagsResult` <-
function(x, typeR = FALSE) {
xi <- if(x@corstruct.tag != "independence")
update(x, corstruct = "independence") else x
.qic2(x@fitted.values + x@residuals, x@fitted.values, x@robust.parmvar,
xi@fitted.values, xi@naive.parmvar, family(x)\$family,
typeR = typeR)
}

`getQIC.geem` <-
function(x, typeR = FALSE) {
fam <- family(x)
xi <- if(x\$corr != "independence")
update(x, corstr = "independence") else x
.qic2(x\$y, fitted(x), x\$var, fitted(xi), xi\$naiv.var,
if(inherits(fam, "family")) fam\$family else "custom",
typeR = typeR)
}

`QIC` <- function (object, ..., typeR = FALSE) {
if (!missing(...)) {
res <- sapply(list(object, ...), getQIC, typeR = typeR)
val <- as.data.frame(t(res[1L,, drop = FALSE]))
colnames(val) <- c("QIC")
Call <- match.call()
Call\$typeR <- NULL
row.names(val) <- as.character(Call[-1L])
val
} else getQIC(object, typeR = typeR)[1L]
}

`QICu` <- function (object, ..., typeR = FALSE) {
if (!missing(...)) {
res <- sapply(list(object, ...), getQIC, typeR = typeR)
val <- as.data.frame(t(res[2L,, drop = FALSE]))
colnames(val) <- "QICu"
Call <- match.call()
Call\$typeR <- NULL
row.names(val) <- as.character(Call[-1L])
val
} else getQIC(object, typeR = typeR)[2L]
}
```

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MuMIn documentation built on July 25, 2018, 1:04 a.m.