Last updated on 2019-11-26 00:51:56 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.5.4 | 7.84 | 43.15 | 50.99 | ERROR | |
| r-devel-linux-x86_64-debian-gcc | 1.5.4 | 5.84 | 33.97 | 39.81 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.5.4 | 63.52 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.5.4 | 61.68 | OK | |||
| r-devel-windows-ix86+x86_64 | 1.5.4 | 24.00 | 94.00 | 118.00 | OK | |
| r-devel-windows-ix86+x86_64-gcc8 | 1.5.4 | 22.00 | 73.00 | 95.00 | OK | |
| r-patched-linux-x86_64 | 1.5.4 | 6.66 | 46.40 | 53.06 | OK | |
| r-patched-solaris-x86 | 1.5.4 | 81.20 | OK | |||
| r-release-linux-x86_64 | 1.5.4 | 7.13 | 46.59 | 53.72 | OK | |
| r-release-windows-ix86+x86_64 | 1.5.4 | 19.00 | 70.00 | 89.00 | OK | |
| r-release-osx-x86_64 | 1.5.4 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 1.5.4 | 11.00 | 90.00 | 101.00 | OK | |
| r-oldrel-osx-x86_64 | 1.5.4 | OK |
Version: 1.5.4
Check: examples
Result: ERROR
Running examples in 'lqmm-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: lqm.counts
> ### Title: Quantile Regression for Counts
> ### Aliases: lqm.counts
> ### Keywords: quantiles for counts
>
> ### ** Examples
>
>
> n <- 100
> x <- runif(n)
> test <- data.frame(x = x, y = rpois(n, 2*x))
> lqm.counts(y ~ x, data = test, M = 50)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
lqmm
--- call from context ---
lqm.counts(y ~ x, data = test, M = 50)
--- call from argument ---
if (class(tmpInv) != "try-error") {
d[, , i] <- tmpInv
} else {
sel[i] <- FALSE
}
--- R stacktrace ---
where 1: lqm.counts(y ~ x, data = test, M = 50)
--- value of length: 2 type: logical ---
[1] TRUE TRUE
--- function from context ---
function (formula, data, weights = NULL, offset = NULL, contrasts = NULL,
tau = 0.5, M = 50, zeta = 1e-05, B = 0.999, cn = NULL, alpha = 0.05,
control = list())
{
nq <- length(tau)
if (nq > 1)
stop("One quantile at a time")
call <- match.call()
mf <- match.call(expand.dots = FALSE)
m <- match(c("formula", "data", "weights"), names(mf), 0L)
mf <- mf[c(1L, m)]
mf$drop.unused.levels <- TRUE
mf[[1L]] <- as.name("model.frame")
mf <- eval(mf, parent.frame())
mt <- attr(mf, "terms")
y <- model.response(mf, "numeric")
w <- as.vector(model.weights(mf))
if (!is.null(w) && !is.numeric(w))
stop("'weights' must be a numeric vector")
if (is.null(w))
w <- rep(1, length(y))
x <- model.matrix(mt, mf, contrasts)
p <- ncol(x)
n <- nrow(x)
term.labels <- colnames(x)
if (is.null(offset))
offset <- rep(0, n)
if (is.null(names(control)))
control <- lqmControl()
else {
control_default <- lqmControl()
control_names <- intersect(names(control), names(control_default))
control_default[control_names] <- control[control_names]
control <- control_default
}
if (is.null(control$loop_step))
control$loop_step <- sd(as.numeric(y))
if (control$beta > 1 || control$beta < 0)
stop("Beta must be a decreasing factor in (0,1)")
if (control$gamma < 1)
stop("Beta must be a nondecreasing factor >= 1")
if (p == 1)
control$loop_tol_ll <- 0.005
theta_0 <- glm.fit(x = as.matrix(x), y = y, weights = w,
offset = offset, family = poisson())$coefficients
Z <- replicate(M, addnoise(y, centered = FALSE, B = B))
TZ <- apply(Z, 2, function(x, off, tau, zeta) log(ifelse((x -
tau) > zeta, x - tau, zeta)) - off, off = offset, tau = tau,
zeta = zeta)
fit <- apply(TZ, 2, function(y, x, weights, tau, control,
theta) lqm.fit.gs(theta = theta, x = x, y = y, weights = weights,
tau = tau, control = control), x = x, weights = w, tau = tau,
control = control, theta = theta_0)
yhat <- sapply(fit, function(obj, x) x %*% obj$theta, x = x)
yhat <- as.matrix(yhat)
eta <- sweep(yhat, 1, offset, "+")
zhat <- tau + exp(eta)
Fvec <- Vectorize(F.lqm)
if (is.null(cn))
cn <- 0.5 * log(log(n))/sqrt(n)
F <- apply(zhat, 2, Fvec, cn = cn)
Fp <- apply(zhat + 1, 2, Fvec, cn = cn)
multiplier <- (tau - (TZ <= yhat))^2
a <- array(NA, dim = c(p, p, M))
for (i in 1:M) a[, , i] <- t(x * multiplier[, i]) %*% x/n
multiplier <- tau^2 + (1 - 2 * tau) * (y <= (zhat - 1)) +
((zhat - y) * (zhat - 1 < y & y <= zhat)) * (zhat - y -
2 * tau)
b <- array(NA, dim = c(p, p, M))
for (i in 1:M) b[, , i] <- t(x * multiplier[, i]) %*% x/n
multiplier <- exp(eta) * (F <= Z & Z < Fp)
d <- array(NA, dim = c(p, p, M))
sel <- rep(TRUE, M)
for (i in 1:M) {
tmpInv <- try(solve(t(x * multiplier[, i]) %*% x/n),
silent = TRUE)
if (class(tmpInv) != "try-error") {
d[, , i] <- tmpInv
}
else {
sel[i] <- FALSE
}
}
dad <- 0
dbd <- 0
for (i in (1:M)[sel]) {
dad <- dad + d[, , i] %*% a[, , i] %*% d[, , i]
dbd <- dbd + d[, , i] %*% b[, , i] %*% d[, , i]
}
m.n <- sum(sel)
if (m.n != 0) {
V <- dad/(m.n^2) + (1 - 1/m.n) * dbd * 1/m.n
V <- V/n
stds <- sqrt(diag(V))
}
else {
stds <- NA
warning("Standard error not available")
}
est <- sapply(fit, function(x) x$theta)
est <- if (p == 1)
mean(est)
else rowMeans(est)
qfit <- if (p == 1) {
tau + exp(mean(eta[1, ]))
}
else {
tau + exp(rowMeans(eta))
}
lower <- est + qt(alpha/2, n - p) * stds
upper <- est + qt(1 - alpha/2, n - p) * stds
tP <- 2 * pt(-abs(est/stds), n - p)
ans <- cbind(est, stds, lower, upper, tP)
colnames(ans) <- c("Value", "Std. Error", "lower bound",
"upper bound", "Pr(>|t|)")
rownames(ans) <- names(est) <- term.labels
fit <- list()
fit$call <- call
fit$na.action <- attr(mf, "na.action")
fit$contrasts <- attr(x, "contrasts")
fit$term.labels <- term.labels
fit$terms <- mt
fit$theta <- est
fit$tau <- tau
fit$nobs <- n
fit$M <- M
fit$Mn <- m.n
fit$rdf <- n - p
fit$x <- x
fit$y <- y
fit$fitted <- qfit
fit$offset <- offset
fit$Cov <- V
fit$tTable <- ans
fit$levels <- .getXlevels(mt, mf)
fit$InitialPar <- list(theta = theta_0)
fit$control <- control
class(fit) <- "lqm.counts"
return(fit)
}
<bytecode: 0x36fb358>
<environment: namespace:lqmm>
--- function search by body ---
Function lqm.counts in namespace lqmm has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: the condition has length > 1
Flavor: r-devel-linux-x86_64-debian-clang
Version: 1.5.4
Check: examples
Result: ERROR
Running examples in ‘lqmm-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: lqm.counts
> ### Title: Quantile Regression for Counts
> ### Aliases: lqm.counts
> ### Keywords: quantiles for counts
>
> ### ** Examples
>
>
> n <- 100
> x <- runif(n)
> test <- data.frame(x = x, y = rpois(n, 2*x))
> lqm.counts(y ~ x, data = test, M = 50)
----------- FAILURE REPORT --------------
--- failure: the condition has length > 1 ---
--- srcref ---
:
--- package (from environment) ---
lqmm
--- call from context ---
lqm.counts(y ~ x, data = test, M = 50)
--- call from argument ---
if (class(tmpInv) != "try-error") {
d[, , i] <- tmpInv
} else {
sel[i] <- FALSE
}
--- R stacktrace ---
where 1: lqm.counts(y ~ x, data = test, M = 50)
--- value of length: 2 type: logical ---
[1] TRUE TRUE
--- function from context ---
function (formula, data, weights = NULL, offset = NULL, contrasts = NULL,
tau = 0.5, M = 50, zeta = 1e-05, B = 0.999, cn = NULL, alpha = 0.05,
control = list())
{
nq <- length(tau)
if (nq > 1)
stop("One quantile at a time")
call <- match.call()
mf <- match.call(expand.dots = FALSE)
m <- match(c("formula", "data", "weights"), names(mf), 0L)
mf <- mf[c(1L, m)]
mf$drop.unused.levels <- TRUE
mf[[1L]] <- as.name("model.frame")
mf <- eval(mf, parent.frame())
mt <- attr(mf, "terms")
y <- model.response(mf, "numeric")
w <- as.vector(model.weights(mf))
if (!is.null(w) && !is.numeric(w))
stop("'weights' must be a numeric vector")
if (is.null(w))
w <- rep(1, length(y))
x <- model.matrix(mt, mf, contrasts)
p <- ncol(x)
n <- nrow(x)
term.labels <- colnames(x)
if (is.null(offset))
offset <- rep(0, n)
if (is.null(names(control)))
control <- lqmControl()
else {
control_default <- lqmControl()
control_names <- intersect(names(control), names(control_default))
control_default[control_names] <- control[control_names]
control <- control_default
}
if (is.null(control$loop_step))
control$loop_step <- sd(as.numeric(y))
if (control$beta > 1 || control$beta < 0)
stop("Beta must be a decreasing factor in (0,1)")
if (control$gamma < 1)
stop("Beta must be a nondecreasing factor >= 1")
if (p == 1)
control$loop_tol_ll <- 0.005
theta_0 <- glm.fit(x = as.matrix(x), y = y, weights = w,
offset = offset, family = poisson())$coefficients
Z <- replicate(M, addnoise(y, centered = FALSE, B = B))
TZ <- apply(Z, 2, function(x, off, tau, zeta) log(ifelse((x -
tau) > zeta, x - tau, zeta)) - off, off = offset, tau = tau,
zeta = zeta)
fit <- apply(TZ, 2, function(y, x, weights, tau, control,
theta) lqm.fit.gs(theta = theta, x = x, y = y, weights = weights,
tau = tau, control = control), x = x, weights = w, tau = tau,
control = control, theta = theta_0)
yhat <- sapply(fit, function(obj, x) x %*% obj$theta, x = x)
yhat <- as.matrix(yhat)
eta <- sweep(yhat, 1, offset, "+")
zhat <- tau + exp(eta)
Fvec <- Vectorize(F.lqm)
if (is.null(cn))
cn <- 0.5 * log(log(n))/sqrt(n)
F <- apply(zhat, 2, Fvec, cn = cn)
Fp <- apply(zhat + 1, 2, Fvec, cn = cn)
multiplier <- (tau - (TZ <= yhat))^2
a <- array(NA, dim = c(p, p, M))
for (i in 1:M) a[, , i] <- t(x * multiplier[, i]) %*% x/n
multiplier <- tau^2 + (1 - 2 * tau) * (y <= (zhat - 1)) +
((zhat - y) * (zhat - 1 < y & y <= zhat)) * (zhat - y -
2 * tau)
b <- array(NA, dim = c(p, p, M))
for (i in 1:M) b[, , i] <- t(x * multiplier[, i]) %*% x/n
multiplier <- exp(eta) * (F <= Z & Z < Fp)
d <- array(NA, dim = c(p, p, M))
sel <- rep(TRUE, M)
for (i in 1:M) {
tmpInv <- try(solve(t(x * multiplier[, i]) %*% x/n),
silent = TRUE)
if (class(tmpInv) != "try-error") {
d[, , i] <- tmpInv
}
else {
sel[i] <- FALSE
}
}
dad <- 0
dbd <- 0
for (i in (1:M)[sel]) {
dad <- dad + d[, , i] %*% a[, , i] %*% d[, , i]
dbd <- dbd + d[, , i] %*% b[, , i] %*% d[, , i]
}
m.n <- sum(sel)
if (m.n != 0) {
V <- dad/(m.n^2) + (1 - 1/m.n) * dbd * 1/m.n
V <- V/n
stds <- sqrt(diag(V))
}
else {
stds <- NA
warning("Standard error not available")
}
est <- sapply(fit, function(x) x$theta)
est <- if (p == 1)
mean(est)
else rowMeans(est)
qfit <- if (p == 1) {
tau + exp(mean(eta[1, ]))
}
else {
tau + exp(rowMeans(eta))
}
lower <- est + qt(alpha/2, n - p) * stds
upper <- est + qt(1 - alpha/2, n - p) * stds
tP <- 2 * pt(-abs(est/stds), n - p)
ans <- cbind(est, stds, lower, upper, tP)
colnames(ans) <- c("Value", "Std. Error", "lower bound",
"upper bound", "Pr(>|t|)")
rownames(ans) <- names(est) <- term.labels
fit <- list()
fit$call <- call
fit$na.action <- attr(mf, "na.action")
fit$contrasts <- attr(x, "contrasts")
fit$term.labels <- term.labels
fit$terms <- mt
fit$theta <- est
fit$tau <- tau
fit$nobs <- n
fit$M <- M
fit$Mn <- m.n
fit$rdf <- n - p
fit$x <- x
fit$y <- y
fit$fitted <- qfit
fit$offset <- offset
fit$Cov <- V
fit$tTable <- ans
fit$levels <- .getXlevels(mt, mf)
fit$InitialPar <- list(theta = theta_0)
fit$control <- control
class(fit) <- "lqm.counts"
return(fit)
}
<bytecode: 0x5595e73d8788>
<environment: namespace:lqmm>
--- function search by body ---
Function lqm.counts in namespace lqmm has this body.
----------- END OF FAILURE REPORT --------------
Fatal error: the condition has length > 1
Flavor: r-devel-linux-x86_64-debian-gcc