Last updated on 2026-06-27 01:50:51 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.1.0 | 121.64 | 160.98 | 282.62 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 0.1.0 | 117.77 | 122.54 | 240.31 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 0.1.0 | 148.00 | 267.13 | 415.13 | NOTE | |
| r-devel-linux-x86_64-fedora-gcc | 0.1.0 | 266.00 | 292.14 | 558.14 | NOTE | |
| r-devel-windows-x86_64 | 0.1.0 | 143.00 | 197.00 | 340.00 | NOTE | |
| r-patched-linux-x86_64 | 0.1.0 | 126.36 | 172.17 | 298.53 | NOTE | |
| r-release-linux-x86_64 | 0.1.0 | 149.79 | 171.23 | 321.02 | NOTE | |
| r-release-macos-arm64 | 0.1.0 | 26.00 | 41.00 | 67.00 | NOTE | |
| r-release-macos-x86_64 | 0.1.0 | 84.00 | 280.00 | 364.00 | NOTE | |
| r-release-windows-x86_64 | 0.1.0 | 147.00 | 198.00 | 345.00 | NOTE | |
| r-oldrel-macos-arm64 | 0.1.0 | NOTE | ||||
| r-oldrel-macos-x86_64 | 0.1.0 | 78.00 | 226.00 | 304.00 | NOTE | |
| r-oldrel-windows-x86_64 | 0.1.0 | 191.00 | 269.00 | 460.00 | NOTE |
Version: 0.1.0
Check: DESCRIPTION meta-information
Result: NOTE
Missing dependency on R >= 4.1.0 because package code uses the pipe
|> or function shorthand \(...) syntax added in R 4.1.0.
File(s) using such syntax:
‘estimate.R’ ‘formula.R’ ‘toy_data.R’
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 0.1.0
Check: examples
Result: ERROR
Running examples in ‘miniLNM-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: beta_mean
> ### Title: LNM Posterior Mean
> ### Aliases: beta_mean
>
> ### ** Examples
>
> example_data <- lnm_data(N = 50, K = 10)
> xy <- dplyr::bind_cols(example_data[c("X", "y")])
> fit <- lnm(
+ starts_with("y") ~ starts_with("x"), xy,
+ iter = 25, output_samples = 25
+ )
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000361 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 3.61 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1:
Chain 1: Drawing a sample of size 25 from the approximate posterior...
Chain 1: COMPLETED.
Error in if (p$diagnostics$pareto_k > 1) { :
missing value where TRUE/FALSE needed
Calls: lnm ... new -> initialize -> initialize -> vb -> vb -> .local
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.1.0
Check: tests
Result: ERROR
Running ‘testthat.R’ [7s/10s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> # This file is part of the standard setup for testthat.
> # It is recommended that you do not modify it.
> #
> # Where should you do additional test configuration?
> # Learn more about the roles of various files in:
> # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview
> # * https://testthat.r-lib.org/articles/special-files.html
>
> library(testthat)
> library(miniLNM)
>
> test_check("miniLNM")
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.004321 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 43.21 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1:
Chain 1: Drawing a sample of size 25 from the approximate posterior...
Chain 1: COMPLETED.
Saving _problems/test-estimate-7.R
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000131 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 1.31 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1:
Chain 1: Drawing a sample of size 25 from the approximate posterior...
Chain 1: COMPLETED.
Saving _problems/test-predict-7.R
Chain 1: ------------------------------------------------------------
Chain 1: EXPERIMENTAL ALGORITHM:
Chain 1: This procedure has not been thoroughly tested and may be unstable
Chain 1: or buggy. The interface is subject to change.
Chain 1: ------------------------------------------------------------
Chain 1:
Chain 1:
Chain 1:
Chain 1: Gradient evaluation took 0.000227 seconds
Chain 1: 1000 transitions using 10 leapfrog steps per transition would take 2.27 seconds.
Chain 1: Adjust your expectations accordingly!
Chain 1:
Chain 1:
Chain 1: Begin eta adaptation.
Chain 1: Iteration: 1 / 250 [ 0%] (Adaptation)
Chain 1: Iteration: 50 / 250 [ 20%] (Adaptation)
Chain 1: Iteration: 100 / 250 [ 40%] (Adaptation)
Chain 1: Iteration: 150 / 250 [ 60%] (Adaptation)
Chain 1: Iteration: 200 / 250 [ 80%] (Adaptation)
Chain 1: Success! Found best value [eta = 1] earlier than expected.
Chain 1:
Chain 1: Begin stochastic gradient ascent.
Chain 1: iter ELBO delta_ELBO_mean delta_ELBO_med notes
Chain 1: Informational Message: The maximum number of iterations is reached! The algorithm may not have converged.
Chain 1: This variational approximation is not guaranteed to be meaningful.
Chain 1:
Chain 1: Drawing a sample of size 25 from the approximate posterior...
Chain 1: COMPLETED.
Saving _problems/test-sample-7.R
[ FAIL 3 | WARN 0 | SKIP 0 | PASS 0 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test-estimate.R:4:1'): (code run outside of `test_that()`) ──────────
Error in `if (p$diagnostics$pareto_k > 1) { warning("Pareto k diagnostic value is ", round(p$diagnostics$pareto_k, 2), ". Resampling is disabled.", " Decreasing tol_rel_obj may help if variational algorithm has terminated prematurely.", " Otherwise consider using sampling instead.", call. = FALSE, immediate. = TRUE) } else if (p$diagnostics$pareto_k > 0.7) { warning("Pareto k diagnostic value is ", round(p$diagnostics$pareto_k, 2), ". Resampling is unreliable.", " Increasing the number of draws or decreasing tol_rel_obj may help.", call. = FALSE, immediate. = TRUE) }`: missing value where TRUE/FALSE needed
Backtrace:
▆
1. └─miniLNM::lnm(...) at test-estimate.R:4:1
2. ├─methods::new(...)
3. │ ├─methods::initialize(value, ...)
4. │ └─methods::initialize(value, ...)
5. ├─rstan::vb(stanmodels$lnm, data_list, ...)
6. └─rstan::vb(stanmodels$lnm, data_list, ...)
7. └─rstan (local) .local(object, ...)
── Error ('test-predict.R:4:1'): (code run outside of `test_that()`) ───────────
Error in `if (p$diagnostics$pareto_k > 1) { warning("Pareto k diagnostic value is ", round(p$diagnostics$pareto_k, 2), ". Resampling is disabled.", " Decreasing tol_rel_obj may help if variational algorithm has terminated prematurely.", " Otherwise consider using sampling instead.", call. = FALSE, immediate. = TRUE) } else if (p$diagnostics$pareto_k > 0.7) { warning("Pareto k diagnostic value is ", round(p$diagnostics$pareto_k, 2), ". Resampling is unreliable.", " Increasing the number of draws or decreasing tol_rel_obj may help.", call. = FALSE, immediate. = TRUE) }`: missing value where TRUE/FALSE needed
Backtrace:
▆
1. └─miniLNM::lnm(...) at test-predict.R:4:1
2. ├─methods::new(...)
3. │ ├─methods::initialize(value, ...)
4. │ └─methods::initialize(value, ...)
5. ├─rstan::vb(stanmodels$lnm, data_list, ...)
6. └─rstan::vb(stanmodels$lnm, data_list, ...)
7. └─rstan (local) .local(object, ...)
── Error ('test-sample.R:4:1'): (code run outside of `test_that()`) ────────────
Error in `if (p$diagnostics$pareto_k > 1) { warning("Pareto k diagnostic value is ", round(p$diagnostics$pareto_k, 2), ". Resampling is disabled.", " Decreasing tol_rel_obj may help if variational algorithm has terminated prematurely.", " Otherwise consider using sampling instead.", call. = FALSE, immediate. = TRUE) } else if (p$diagnostics$pareto_k > 0.7) { warning("Pareto k diagnostic value is ", round(p$diagnostics$pareto_k, 2), ". Resampling is unreliable.", " Increasing the number of draws or decreasing tol_rel_obj may help.", call. = FALSE, immediate. = TRUE) }`: missing value where TRUE/FALSE needed
Backtrace:
▆
1. └─miniLNM::lnm(...) at test-sample.R:4:1
2. ├─methods::new(...)
3. │ ├─methods::initialize(value, ...)
4. │ └─methods::initialize(value, ...)
5. ├─rstan::vb(stanmodels$lnm, data_list, ...)
6. └─rstan::vb(stanmodels$lnm, data_list, ...)
7. └─rstan (local) .local(object, ...)
[ FAIL 3 | WARN 0 | SKIP 0 | PASS 0 ]
Error:
! Test failures.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc