* using log directory ‘/data/localhost/ripley/R/packages/tests-MKL/dacc.Rcheck’
* using R Under development (unstable) (2026-11-08 r90859)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc (GCC) 16.2.1 20261029 (Red Hat 16.2.1-3)
    GNU Fortran (GCC) 16.2.1 20261029 (Red Hat 16.2.1-3)
* running under: Fedora Linux 44 (Server Edition)
* using session charset: UTF-8
* current time: 2026-11-09 05:34:39 UTC
* using option ‘--no-stop-on-test-error’
* checking for file ‘dacc/DESCRIPTION’ ... OK
* this is package ‘dacc’ version ‘0.1.0’
* package encoding: UTF-8
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘dacc’ can be installed ... [6s/15s] OK
* checking package directory ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... OK
* checking whether the package can be loaded with stated dependencies ... OK
* checking whether the package can be unloaded cleanly ... OK
* checking whether the namespace can be loaded with stated dependencies ... OK
* checking whether the namespace can be unloaded cleanly ... OK
* checking loading without being on the library search path ... OK
* checking use of S3 registration ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [12s/32s] OK
* checking Rd files ... OK
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... OK
* checking data for ASCII and uncompressed saves ... OK
* checking examples ... OK
* checking for unstated dependencies in ‘tests’ ... OK
* checking tests ...
  Running ‘dispatch.R’
  Running ‘factor-selection.R’
  Running ‘inflation-arguments.R’
  Running ‘latent.R’
  Running ‘poly.R’
 [9s/22s] ERROR
Running the tests in ‘tests/dispatch.R’ failed.
Complete output:
  > if (file.exists(file.path("R", "fingerprint.R"))) {
  +     for (file in list.files("R", pattern = "[.]R$", full.names = TRUE)) {
  +         source(file)
  +     }
  + } else {
  +     library(dacc)
  + }
  > 
  > # Test routing independently of the numerical implementations.
  > routing <- new.env(parent = environment(fingerprint))
  > routing$fingerprintPoly <- function(...) list(backend = "poly", arguments = list(...))
  > routing$fingerprintLatent <- function(...) list(backend = "latent", arguments = list(...))
  > routing$fingerprintLegacy <- function(...) list(backend = "legacy", arguments = list(...))
  > route <- fingerprint
  > environment(route) <- routing
  > X <- matrix(seq_len(20), 10, 2)
  > Y <- seq_len(10)
  > Z <- matrix(0, 30, 10)
  > 
  > fit <- route(X, Y, c(3, 4), Z, degree = 3, estimate.inflation = FALSE)
  > stopifnot(fit$backend == "poly", fit$arguments$degree == 3)
  > fit <- route(X, Y, c(3, 4), Z, method = "latent", n.factors = 2)
  > stopifnot(fit$backend == "latent", fit$arguments$n.factors == 2)
  > for (method in c("EE", "PBC", "TS", "TS.TempSt")) {
  +     fit <- route(X, Y, c(3, 4), Z, method = method, S = 2, T = 5)
  +     stopifnot(
  +         fit$backend == "legacy", fit$arguments$method == method,
  +         identical(fit$arguments$ctlruns.sigma, Z),
  +         identical(fit$arguments$ctlruns.bhvar, Z)
  +     )
  + }
  > stopifnot(
  +     identical(eval(formals(fingerprint)$method),
  +         c("poly", "linear", "latent", "EE", "PBC", "TS", "TS.TempSt")),
  +     !"legacy.method" %in% names(formals(fingerprint)),
  +     inherits(try(route(X, Y, c(3, 4), Z, method = "legacy"),
  +         silent = TRUE), "try-error")
  + )
  > 
  > # The explicit linear method fixes degree one without fixing inflation coefficients.
  > for (estimate in c(TRUE, FALSE)) {
  +     fit <- route(X, Y, c(3, 4), Z, method = "linear",
  +                  estimate.inflation = estimate)
  +     stopifnot(fit$backend == "poly", fit$arguments$degree == 1L,
  +               identical(fit$arguments$estimate.inflation, estimate))
  + }
  > for (degree in list(3, 0, NA_real_, NULL, "1", c(1, 3))) {
  +     fit <- route(X, Y, c(3, 4), Z, method = "linear", degree = degree)
  +     stopifnot(fit$backend == "poly", identical(fit$arguments$degree, 1L))
  + }
  > fit <- route(X, Y, c(3, 4), Z, method = "linear", degree = 1)
  > stopifnot(fit$arguments$degree == 1L)
  > 
  > # Renaming the polynomial backend must not change its estimates.
  > set.seed(89)
  > X <- cbind(3 * sin(seq_len(40) / 4), 3 * cos(seq_len(40) / 5))
  > Y <- as.vector(X %*% c(1, 0.5) + rnorm(40))
  > Z <- matrix(rnorm(120 * 40), 120)
  > a <- fingerprint(X, Y, c(30, 30), Z, degree = 1, estimate.inflation = FALSE)
  > b <- fingerprintPoly(X, Y, c(30, 30), Z, degree = 1, estimate.inflation = FALSE)
  > stopifnot(
  +     inherits(a, "fingerprintPoly"), inherits(a, "fingerprint"),
  +     identical(a$beta, b$beta), identical(a$var, b$var), identical(a$ci, b$ci)
  + )
  > 
  > linear <- fingerprint(X, Y, c(30, 30), Z,
  +                       method = "linear", degree = 3, estimate.inflation = FALSE)
  > stopifnot(identical(linear$beta, b$beta), identical(linear$var, b$var),
  +           identical(linear$ci, b$ci))
  > 
  > # Original estimator and bootstrap intervals remain unchanged by dispatch.
  > Y <- matrix(Y, ncol = 1)
  > set.seed(55)
  > a <- fingerprint(
  +     X, Y, c(30, 30), Z, method = "TS",
  +     S = 4, T = 10, B = 5, cov.method = "l2"
  + )
  > set.seed(55)
  > b <- fingerprintLegacy(
  +     X, Y, c(30, 30), Z, Z, 4, 10,
  +     B = 5, method = "TS", cov.method = "l2"
  + )
  > stopifnot(identical(a, b))
  Error: identical(a, b) is not TRUE
  Execution halted
Running the tests in ‘tests/latent.R’ failed.
Complete output:
  > if (file.exists(file.path("R", "fingerprintLatent.R"))) {
  +     for (file in list.files("R", pattern = "[.]R$", full.names = TRUE)) source(file)
  + } else {
  +     library(dacc)
  +     for (name in c(".lf_spikes", ".lf_spike_roots", ".lf_traces")) {
  +         assign(name, getFromNamespace(name, "dacc"))
  +     }
  + }
  > 
  > # Trace formulas (10)--(13) against direct matrices with known alignments.
  > set.seed(15)
  > N <- 30L
  > basis <- qr.Q(qr(matrix(rnorm(N * 4), N)))
  > true.U <- basis[, 1:2]
  > z <- c(0.8, 0.6)
  > empirical.U <- sweep(true.U, 2, sqrt(z), "*") +
  +     sweep(basis[, 3:4], 2, sqrt(1 - z), "*")
  > pi <- c(7, 4)
  > noise <- 1.3
  > theta <- c(-1, 0.4)
  > C <- noise * diag(N) + true.U %*% diag(pi) %*% t(true.U)
  > W <- diag(N) + empirical.U %*% diag(theta) %*% t(empirical.U)
  > Wt <- empirical.U %*% diag(pi / z * (z * theta + 1)^2) %*%
  +     t(empirical.U) + noise * W %*% W
  > tr <- .lf_traces(theta, pi, noise, z, N)
  > stopifnot(
  +     abs(tr$delta - sum(diag(W %*% C)) / N) < 1e-12,
  +     abs(tr$phi - sum(diag(W %*% C %*% W %*% C)) / N) < 1e-12,
  +     abs(tr$psi - sum(diag(Wt %*% C)) / N) < 1e-12
  + )
  > 
  > # Algorithm 1, including the noise bias adjustment.
  > known.pi <- c(15, 8)
  > gamma <- 0.5
  > noise0 <- 2
  > leading <- noise0 + known.pi + gamma * noise0 * (known.pi + noise0) / known.pi
  > stopifnot(max(abs(.lf_spike_roots(leading, noise0, gamma) - known.pi)) < 1e-12)
  > corrected <- .lf_spikes(c(leading, rep(noise0, 38)), 2, 80)
  > expected.noise <- noise0 * (1 + gamma * (2 + sum(noise0 / known.pi)) / 38)
  > stopifnot(abs(corrected$noise - expected.noise) < 1e-12)
  > 
  > # Detectable factors, unequal ensemble sizes, and variance heterogeneity.
  > set.seed(95)
  > N <- 120L
  > m <- 180L
  > K <- 2L
  > sizes <- c(25L, 35L)
  > U <- qr.Q(qr(matrix(rnorm(N * K), N)))
  > Sigma <- diag(N) + U %*% diag(c(18, 12)) %*% t(U)
  > L <- chol(Sigma)
  > truth <- cbind(3 * sin(seq_len(N) / 8), 4 * cos(seq_len(N) / 11))
  > Z <- matrix(rnorm(m * N), m) %*% L * sqrt(1.5)
  > ensembles <- lapply(seq_len(2), function(i) {
  +     sweep(matrix(rnorm(sizes[i] * N), sizes[i]) %*% L * sqrt(1.8),
  +           2, truth[, i], "+")
  + })
  > X <- vapply(ensembles, colMeans, numeric(N))
  > Y <- as.vector(truth %*% c(1, 0.7)) + as.vector(rnorm(N) %*% L)
  > fixed <- fingerprintLatent(
  +     X, Y, sizes, Z, n.factors = K,
  +     estimate.inflation = FALSE, theta = c(-0.7, -1)
  + )
  > stopifnot(
  +     inherits(fixed, "fingerprint"), inherits(fixed, "fingerprintLatent"),
  +     fixed$sigma.x2 == 1, fixed$sigma.z2 == 1,
  +     !any(c("Q", "V", "history", "settings", "diagnostic") %in% names(fixed)),
  +     all(is.finite(fixed$ci))
  + )
  > 
  > # Independent precision-weighted SVD solution, including a removed direction.
  > e <- eigen(fixed$weight, symmetric = TRUE)
  > A <- sweep(crossprod(e$vectors, cbind(sweep(X, 2, sqrt(sizes), "*"), Y)),
  +            1, sqrt(pmax(e$values, 0)), "*")
  > v <- svd(A)$v[, 3]
  > reference <- -sqrt(sizes) * v[1:2] / v[3]
  > stopifnot(max(abs(reference - fixed$beta)) < 1e-8)
  > 
  > # Theorem 4 against a direct matrix calculation, including D in Omega.
  > S <- crossprod(Z) / m
  > e <- eigen(S, symmetric = TRUE)
  > sp <- .lf_spikes(pmax(e$values, 0), K, m)
  > Ut <- e$vectors[, seq_len(K), drop = FALSE]
  > t <- fixed$theta
  > tr <- .lf_traces(t, sp$spikes, sp$noise, sp$alignment, N)
  > D <- diag(1 / sizes)
  > G <- crossprod(X, fixed$weight %*% X) / N - tr$delta * D
  > Wt <- Ut %*% diag(sp$spikes / sp$alignment * (sp$alignment * t + 1)^2) %*%
  +     t(Ut) + sp$noise * fixed$weight %*% fixed$weight
  > Omega <- crossprod(X, Wt %*% X) / N - tr$psi * D
  > scale <- 1 + sum(fixed$beta^2 / sizes)
  > Xi <- scale * solve(G) %*% (
  +     Omega + tr$phi * solve(diag(sizes) + tcrossprod(fixed$beta))
  + ) %*% solve(G)
  > stopifnot(max(abs(fixed$var - Xi / N)) < 1e-10)
  > Q <- as.numeric(crossprod(fixed$residuals, fixed$weight %*% fixed$residuals)) / N -
  +     scale * tr$delta
  > V <- 2 / N * scale^2 * tr$phi
  > stopifnot(
  +     abs(fixed$diagnostic.stat - Q / sqrt(V)) < 1e-10,
  +     max(abs(fixed$standardized.residuals - fixed$residuals / sqrt(diag(S)))) < 1e-12
  + )
  > 
  > # Factor estimation and weight selection; exact matching degenerates the test.
  > fit <- fingerprintLatent(X, Y, sizes, Z, K, ensembles = ensembles)
  > within <- sum(vapply(seq_len(2), function(i) {
  +     sum(sweep(ensembles[[i]], 2, X[, i])^2)
  + }, numeric(1))) / (N * (sum(sizes) - 2))
  > stopifnot(
  +     fit$sigma.x2 > 0, fit$sigma.z2 > 0,
  +     all(is.finite(fit$ci)), all(fit$theta >= -1),
  +     abs(fit$p.value - 0.5) < 1e-6,
  +     abs(fit$sigma.x2 / fit$sigma.z2 - within / mean(diag(S))) < 1e-10
  + )
  > dispatched <- fingerprint(X, Y, sizes, Z, method = "latent", n.factors = K,
  +                           ensembles = ensembles)
  > stopifnot(identical(fit$beta, dispatched$beta), identical(fit$var, dispatched$var))
  Error: identical(fit$beta, dispatched$beta) is not TRUE
  Execution halted
* checking PDF version of manual ... OK
* checking HTML version of manual ... OK
* checking for non-standard things in the check directory ... OK
* checking for detritus in the temp directory ... OK
* DONE

Status: 1 ERROR
See
  ‘/data/localhost/ripley/R/packages/tests-MKL/dacc.Rcheck/00check.log’
for details.

Command exited with non-zero status 1
Time 2:23.76, 52.05 + 6.69