Nothing
robmixglm <-
function(formula,family=c("gaussian","binomial","poisson","gamma","truncpoisson","nbinom"),data,offset=NULL,quadpoints=21,
notrials=50,EMTol=1.0e-4, cores = max(detectCores() %/% 2, 1), verbose=FALSE) {
is.wholenumber <- function(x, tol = .Machine$double.eps^0.5) abs(x - round(x)) < tol
if (cores > max(detectCores() - 1, 1)) {
cores <- max(detectCores() - 1, 1)
warning(sprintf("cores greater than available, setting to %i cores",max(detectCores() - 1, 1)))
}
call <- match.call()
if (missing(family)) family <- "gaussian"
if (!(family %in% c("gaussian","binomial","poisson","gamma","truncpoisson","nbinom")))
stop("Valid families are gaussian, binomial, poisson, gamma, truncpoisson, nbinom.\n")
if (missing(data)) data <- environment(formula)
mf <- match.call(expand.dots = FALSE)
m <- match(c("formula","data","offset"), names(mf), 0L)
mf <- mf[c(1L,m)]
mf$drop.unused.levels <- TRUE
mf[[1L]] <- quote(stats::model.frame)
mf <- eval(mf, parent.frame())
mt <- attr(mf, "terms")
Y <- model.response(mf, "any")
X <- model.matrix(mt,mf)
offset <- model.extract(mf,"offset")
if(is.null(offset)) offset <- rep(0.0,dim(X)[1])
if (family=="binomial") {
if (!inherits(Y,"matrix")) stop("Binomial data must be in success failure form.")
if (dim(Y)[2]!=2) stop("Binomial data must be in success failure form.")
if (any(Y[,1] <0) | any(Y[,2] <0)) stop("Binomial data must be positive.")
if (any(!is.wholenumber(Y[,1]) | !is.wholenumber(Y[,2]))) stop("Binomial data must be integers.")
} else if ((!inherits(Y,"numeric") & !inherits(Y,"integer"))) stop("Data must be a single column")
if (family=="poisson") {
if (any(Y <0)) stop("Poisson data must be positive.")
if (any(!is.wholenumber(Y))) stop("Poisson data must be integers.")
}
if (family=="gamma") {
if (any(Y <0)) stop("Gamma data must be positive.")
}
if (family=="truncpoisson") {
if (any(Y<=0)) stop("Truncated poisson data must be positive non-zero.")
if (any(!is.wholenumber(Y))) stop("Truncated poisson data must be integers.")
}
if (family=="nbinom") {
if (any(Y <0)) stop("Negative binomial data must be positive.")
if (any(!is.wholenumber(Y))) stop("Negative binomial data must be integers.")
}
if (verbose & (cores>1)){
warning("Setting cores=1 to allow Verbose output")
cores <- 1
}
ret <- fit.robmixglm(X,Y,family,offset=offset,gh=norm.gauss.hermite(quadpoints),notrials,EMTol,cores,verbose)
class(ret) <- "robmixglm"
ret$call <- call
ret$family <- family
ret$X <- X
ret$Y <- Y
ret$offset <- offset
ret$model <- mf
ret$terms <- mt
ret$xlevels <- .getXlevels(mt, mf)
ret$quadpoints <- quadpoints
ret$notrials <- notrials
ret$EMTol <- EMTol
ret$verbose <- verbose
return(ret)
}
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