https://github.com/cran/aster
Tip revision: cd7e4fc006dc5296865fa6523ce7d087d86d3ca8 authored by Charles J. Geyer on 20 October 2012, 00:00:00 UTC
version 0.8-20
version 0.8-20
Tip revision: cd7e4fc
is.zero.R
### implements test of (35) of the design doc
is.zero <- function(alphabeenu, fixed, random, obj, y, origin, zwz,
tolerance = sqrt(.Machine$double.eps))
{
stopifnot(inherits(obj, "aster"))
if (missing(y)) {
y <- obj$x
} else {
stopifnot(is.matrix(y))
stopifnot(is.numeric(y))
stopifnot(is.finite(y))
stopifnot(dim(y) == dim(obj$x))
}
if (missing(origin)) {
origin <- obj$origin
} else {
stopifnot(is.matrix(origin))
stopifnot(is.numeric(origin))
stopifnot(is.finite(origin))
stopifnot(dim(origin) == dim(obj$origin))
}
stopifnot(is.matrix(fixed))
stopifnot(is.numeric(fixed))
stopifnot(is.finite(fixed))
nfix <- ncol(fixed)
stopifnot(is.matrix(random) | is.list(random))
if (! is.list(random))
random <- list(random)
for (i in seq(along = random)) {
foo <- random[[i]]
if (! is.matrix(foo))
stop("random not matrix or list of matrices")
if (! is.numeric(foo))
stop("random not numeric matrix or list of such")
if (! all(is.finite(foo)))
stop("some random effects model matrix not all finite")
if (nrow(foo) != nrow(fixed))
stop("fixed and random effects model matrices with different nrow")
}
nrand <- sapply(random, ncol)
stopifnot(is.matrix(zwz))
stopifnot(is.numeric(zwz))
stopifnot(is.finite(zwz))
if (any(dim(zwz) != sum(nrand)))
stop("zwz not square matrix with dimension = number of random effects")
stopifnot(is.vector(alphabeenu))
stopifnot(is.numeric(alphabeenu))
stopifnot(is.finite(alphabeenu))
if (length(alphabeenu) != nfix + sum(nrand) + length(nrand))
stop("alphabeenu wrong length")
idx <- seq(along = alphabeenu)
is.alpha <- idx <= nfix
is.bee <- nfix < idx & idx <= nfix + sum(nrand)
is.nu <- nfix + sum(nrand) < idx
alpha <- alphabeenu[is.alpha]
bee <- alphabeenu[is.bee]
nu <- alphabeenu[is.nu]
dee <- rep(nu, times = nrand)
if (all(nu > tolerance))
return(rep(FALSE, length(nu)))
if (any(nu < (- tolerance)))
stop("apparently negative components of nu, impossible")
nu[nu < tolerance] <- 0
modmat <- cbind(fixed, Reduce(cbind, random))
### note: despite documentation of the mlogl function, it actually
### works to have modmat a matrix rather than a 3-way array
mout <- mlogl(c(alpha, bee), obj$pred, obj$fam, y, obj$root, modmat,
deriv = 2, famlist = obj$famlist, origin = origin)
idx <- seq(along = mout$gradient)
is.bee <- nfix < idx
pb <- mout$gradient[is.bee]
bigh <- sweep(zwz, 2, dee, "*") + diag(length(dee))
bigh.inv <- solve(bigh)
idx <- rep(seq(along = nu), times = nrand)
pn <- rep(NaN, length(nu))
for (k in seq(along = nu)) {
eek <- as.numeric(idx == k)
fook <- sweep(zwz, 2, eek, "*")
pn[k] <- sum(t(bigh.inv) * fook) / 2
}
result <- rep(FALSE, length(nu))
for (k in seq(along = nu))
if (nu[k] == 0)
result[k] <- pn[k] >= sum(pb[idx == k]^2) / 4
return(result)
}