https://github.com/cran/aster
Tip revision: 7016e6b97f24943bdab11323884baf030f38260b authored by Charles J. Geyer on 06 July 2018, 07:20:08 UTC
version 1.0-2
version 1.0-2
Tip revision: 7016e6b
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)
}