Last updated on 2026-07-23 19:50:49 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.1-4 | 13.99 | 223.78 | 237.77 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.1-4 | 10.20 | 162.45 | 172.65 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.1-4 | 28.00 | 369.32 | 397.32 | OK | |
| r-devel-linux-x86_64-fedora-gcc | 1.1-4 | 11.00 | 159.99 | 170.99 | OK | |
| r-devel-windows-x86_64 | 1.1-4 | 19.00 | 253.00 | 272.00 | OK | |
| r-patched-linux-x86_64 | 1.1-4 | 17.46 | 216.75 | 234.21 | OK | |
| r-release-linux-x86_64 | 1.1-4 | 15.10 | 213.55 | 228.65 | OK | |
| r-release-macos-arm64 | 1.1-4 | 4.00 | 67.00 | 71.00 | OK | |
| r-release-macos-x86_64 | 1.1-4 | 11.00 | 294.00 | 305.00 | OK | |
| r-release-windows-x86_64 | 1.1-4 | 18.00 | 261.00 | 279.00 | OK | |
| r-oldrel-macos-arm64 | 1.1-4 | 4.00 | 67.00 | 71.00 | OK | |
| r-oldrel-macos-x86_64 | 1.1-4 | 11.00 | 218.00 | 229.00 | OK | |
| r-oldrel-windows-x86_64 | 1.1-4 | 25.00 | 331.00 | 356.00 | OK |
Version: 1.1-4
Check: tests
Result: ERROR
Running ‘factorize_test_irregular.R’ [2s/3s]
Running ‘factorize_test_regular.R’ [2s/3s]
Running ‘general_tests.R’ [14s/17s]
Running the tests in ‘tests/factorize_test_irregular.R’ failed.
Complete output:
> library(FDboost)
Loading required package: mboost
Loading required package: parallel
Loading required package: stabs
This is FDboost 1.1-4.
>
> # generate irregular toy data -------------------------------------------------------
>
> n <- 100
> m <- 40
> # covariates
> x <- seq(0,2,len = n)
> # time & id
> set.seed(90384)
> t <- runif(n = n*m, -pi,pi)
> id <- sample(1:n, size = n*m, replace = TRUE)
>
> # generate components
> fx <- ft <- list()
> fx[[1]] <- exp(x)
> d <- numeric(2)
> d[1] <- sqrt(c(crossprod(fx[[1]])))
> fx[[1]] <- fx[[1]] / d[1]
> fx[[2]] <- -5*x^2
> fx[[2]] <- fx[[2]] - fx[[1]] * c(crossprod(fx[[1]], fx[[2]])) # orthogonalize fx[[2]]
> d[2] <- sqrt(c(crossprod(fx[[2]])))
> fx[[2]] <- fx[[2]] / d[2]
> ft[[1]] <- sin(t)
> ft[[2]] <- cos(t)
> ft[[1]] <- ft[[1]] / sqrt(sum(ft[[1]]^2))
> ft[[2]] <- ft[[2]] / sqrt(sum(ft[[2]]^2))
>
> mu1 <- d[1] * fx[[1]][id] * ft[[1]]
> mu2 <- d[2] * fx[[2]][id] * ft[[2]]
> # add linear covariate
> ft[[3]] <- t^2 * sin(4*t)
> ft[[3]] <- ft[[3]] - ft[[1]] * c(crossprod(ft[[1]], ft[[3]]))
> ft[[3]] <- ft[[3]] - ft[[2]] * c(crossprod(ft[[2]], ft[[3]]))
> ft[[3]] <- ft[[3]] / sqrt(sum(ft[[3]]^2))
> set.seed(9234)
> fx[[3]] <- runif(0,3, n = length(x))
> fx[[3]] <- fx[[3]] - fx[[1]] * c(crossprod(fx[[1]], fx[[3]]))
> fx[[3]] <- fx[[3]] - fx[[2]] * c(crossprod(fx[[2]], fx[[3]]))
> d[3] <- sqrt(sum(fx[[3]]^2))
> fx[[3]] <- fx[[3]] / d[3]
>
> mu3 <- d[3] * fx[[3]][id] * ft[[3]]
>
> mu <- mu1 + mu2 + mu3
> # add some noise
> y <- mu + rnorm(length(mu), 0, .01)
> # and noise covariate
> z <- rnorm(n)
>
> # fit FDboost model -------------------------------------------------------
>
> dat <- list(y = y, x = x, t = t, x_lin = fx[[3]], id = id)
> m <- FDboost(y ~ bbs(x, knots = 5, df = 2, differences = 0) +
+ # bbs(z, knots = 2, df = 2, differences = 0) +
+ bols(x_lin, intercept = FALSE, df = 2)
+ , ~ bbs(t),
+ id = ~ id,
+ offset = 0, #numInt = "Riemann",
+ control = boost_control(nu = 1),
+ data = dat)
> MU <- split(mu, id)
> PRED <- split(predict(m), id)
> Ti <- split(t, id)
> t0 <- seq(-pi, pi, length.out = 40)
> MU <- do.call(cbind, Map(function(mu, t) approx(t, mu, t0)$y,
+ MU, Ti))
> PRED <- do.call(cbind, Map(function(mu, t) approx(t, mu, t0)$y,
+ PRED, Ti))
>
> opar <- par(mfrow = c(2,2))
> image(t0, x, MU)
> contour(t0, x, MU, add = TRUE)
> image(t0, x, PRED)
> contour(t0, x, PRED, add = TRUE)
> persp(t0, x, MU, zlim = range(c(MU, PRED), na.rm = TRUE))
> persp(t0, x, PRED, zlim = range(c(MU, PRED), na.rm = TRUE))
> par(opar)
>
> # factorize model ---------------------------------------------------------
>
> fac <- factorize(m)
Warning message:
In df2lambda(X, df = args$df, lambda = args$lambda, dmat = K, weights = w, :*** buffer overflow detected ***: terminated
Aborted
Running the tests in ‘tests/factorize_test_regular.R’ failed.
Complete output:
> library(FDboost)
Loading required package: mboost
Loading required package: parallel
Loading required package: stabs
This is FDboost 1.1-4.
>
> # generate regular toy data --------------------------------------------------
>
> n <- 100
> m <- 40
> # covariates
> x <- seq(0,2,len = n)
> # time
> t <- seq(-pi,pi,len = m)
> # generate components
> fx <- ft <- list()
> fx[[1]] <- exp(x)
> d <- numeric(2)
> d[1] <- sqrt(c(crossprod(fx[[1]])))
> fx[[1]] <- fx[[1]] / d[1]
> fx[[2]] <- -5*x^2
> fx[[2]] <- fx[[2]] - fx[[1]] * c(crossprod(fx[[1]], fx[[2]])) # orthogonalize fx[[2]]
> d[2] <- sqrt(c(crossprod(fx[[2]])))
> fx[[2]] <- fx[[2]] / d[2]
> ft[[1]] <- sin(t)
> ft[[2]] <- cos(t)
> ft[[1]] <- ft[[1]] / sqrt(sum(ft[[1]]^2))
> ft[[2]] <- ft[[2]] / sqrt(sum(ft[[2]]^2))
> mu1 <- d[1] * fx[[1]] %*% t(ft[[1]])
> mu2 <- d[2] * fx[[2]] %*% t(ft[[2]])
> # add linear covariate
> ft[[3]] <- t^2 * sin(4*t)
> ft[[3]] <- ft[[3]] - ft[[1]] * c(crossprod(ft[[1]], ft[[3]]))
> ft[[3]] <- ft[[3]] - ft[[2]] * c(crossprod(ft[[2]], ft[[3]]))
> ft[[3]] <- ft[[3]] / sqrt(sum(ft[[3]]^2))
> set.seed(9234)
> fx[[3]] <- runif(0,3, n = length(x))
> fx[[3]] <- fx[[3]] - fx[[1]] * c(crossprod(fx[[1]], fx[[3]]))
> fx[[3]] <- fx[[3]] - fx[[2]] * c(crossprod(fx[[2]], fx[[3]]))
> d[3] <- sqrt(sum(fx[[3]]^2))
> fx[[3]] <- fx[[3]] / d[3]
> mu3 <- d[3] * fx[[3]] %*% t(ft[[3]])
>
> mu <- mu1 + mu2 + mu3
> # add some noise
> y <- mu + rnorm(length(mu), 0, .01)
> # and noise covariate
> z <- rnorm(n)
>
> # fit FDboost model -------------------------------------------------------
>
> dat <- list(y = y, x = x, t = t, x_lin = fx[[3]])
> m <- FDboost(y ~ bbs(x, knots = 5, df = 2, differences = 0) +
+ # bbs(z, knots = 2, df = 2, differences = 0) +
+ bols(x_lin, intercept = FALSE, df = 2)
+ , ~ bbs(t), offset = 0,
+ control = boost_control(nu = 1),
+ data = dat)
>
> opar <- par(mfrow = c(1,2))
> image(t, x, t(mu))
> contour(t, x, t(mu), add = TRUE)
> image(t, x, t(predict(m)))
> contour(t, x, t(predict(m)), add = TRUE)
> par(opar)
>
> # factorize model ---------------------------------------------------------
>
> fac <- factorize(m)
Warning message:
In df2lambda(X, df = args$df, lambda = args$lambda, dmat = K, weights = w, :*** buffer overflow detected ***: terminated
Aborted
Flavor: r-devel-linux-x86_64-debian-gcc