Last updated on 2025-08-23 12:48:41 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.0.4 | 81.96 | 409.29 | 491.25 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.0.4 | 52.11 | 279.93 | 332.04 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.0.4 | 834.16 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.0.4 | 638.32 | OK | |||
| r-devel-windows-x86_64 | 1.0.4 | 95.00 | 390.00 | 485.00 | OK | |
| r-patched-linux-x86_64 | 1.0.4 | 84.16 | 380.85 | 465.01 | OK | |
| r-release-linux-x86_64 | 1.0.4 | 81.45 | 385.00 | 466.45 | OK | |
| r-release-macos-arm64 | 1.0.4 | 192.00 | OK | |||
| r-release-macos-x86_64 | 1.0.4 | 446.00 | OK | |||
| r-release-windows-x86_64 | 1.0.4 | 96.00 | 398.00 | 494.00 | OK | |
| r-oldrel-macos-arm64 | 1.0.4 | 185.00 | NOTE | |||
| r-oldrel-macos-x86_64 | 1.0.4 | 412.00 | NOTE | |||
| r-oldrel-windows-x86_64 | 1.0.4 | 113.00 | 440.00 | 553.00 | ERROR |
Version: 1.0.4
Check: installed package size
Result: NOTE
installed size is 9.7Mb
sub-directories of 1Mb or more:
doc 4.4Mb
libs 4.1Mb
Flavors: r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64
Version: 1.0.4
Check: tests
Result: ERROR
Running 'testthat.R' [253s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> # CRAN OMP THREAD LIMIT
> Sys.setenv("OMP_THREAD_LIMIT" = 1)
>
> library(testthat)
> library(shapr)
Attaching package: 'shapr'
The following object is masked from 'package:testthat':
setup
>
> test_check("shapr")
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain_forecast()` ----------------------------------------
i Feature names extracted from the model contains `NA`.
Consistency checks between model and data is therefore disabled.
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 128`, and is therefore set to `2^n_features = 128`.
-- Explanation overview --
* Model class: <Arima>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 7
* Number of observations to explain: 2
-- Main computation started --
i Using 128 of 128 coalitions.
-- Starting `shapr::explain_forecast()` ----------------------------------------
i Feature names extracted from the model contains `NA`.
Consistency checks between model and data is therefore disabled.
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 64`, and is therefore set to `2^n_features = 64`.
-- Explanation overview --
* Model class: <Arima>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 6
* Number of observations to explain: 2
-- Main computation started --
i Using 64 of 64 coalitions.
-- Starting `shapr::explain_forecast()` ----------------------------------------
i Feature names extracted from the model contains `NA`.
Consistency checks between model and data is therefore disabled.
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <Arima>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 2
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain_forecast()` ----------------------------------------
i Feature names extracted from the model contains `NA`.
Consistency checks between model and data is therefore disabled.
i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 4`, and is therefore set to `2^n_groups = 4`.
-- Explanation overview --
* Model class: <Arima>
* Approach: empirical
* Iterative estimation: FALSE
* Number of group-wise Shapley values: 2
* Number of observations to explain: 2
-- Main computation started --
i Using 4 of 4 coalitions.
-- Starting `shapr::explain_forecast()` ----------------------------------------
i Feature names extracted from the model contains `NA`.
Consistency checks between model and data is therefore disabled.
i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 4`, and is therefore set to `2^n_groups = 4`.
-- Explanation overview --
* Model class: <Arima>
* Approach: empirical
* Iterative estimation: FALSE
* Number of group-wise Shapley values: 2
* Number of observations to explain: 2
-- Main computation started --
i Using 4 of 4 coalitions.
-- Starting `shapr::explain_forecast()` ----------------------------------------
i Feature names extracted from the model contains `NA`.
Consistency checks between model and data is therefore disabled.
i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 4`, and is therefore set to `2^n_groups = 4`.
-- Explanation overview --
* Model class: <Arima>
* Approach: empirical
* Iterative estimation: FALSE
* Number of group-wise Shapley values: 2
* Number of observations to explain: 2
-- Main computation started --
i Using 4 of 4 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
-- Explanation overview --
* Model class: <lm>
* Approach: independence
* Iterative estimation: TRUE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- iterative computation started --
-- Iteration 1 -----------------------------------------------------------------
i Using 6 of 32 coalitions, 6 new.
-- Iteration 2 -----------------------------------------------------------------
i Using 8 of 32 coalitions, 2 new.
-- Iteration 3 -----------------------------------------------------------------
i Using 10 of 32 coalitions, 2 new.
-- Iteration 4 -----------------------------------------------------------------
i Using 12 of 32 coalitions, 2 new.
-- Iteration 5 -----------------------------------------------------------------
i Using 14 of 32 coalitions, 2 new.
-- Iteration 6 -----------------------------------------------------------------
i Using 16 of 32 coalitions, 2 new.
-- Iteration 7 -----------------------------------------------------------------
i Using 18 of 32 coalitions, 2 new.
-- Iteration 8 -----------------------------------------------------------------
i Using 20 of 32 coalitions, 2 new.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian
* Iterative estimation: TRUE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- iterative computation started --
-- Iteration 1 -----------------------------------------------------------------
i Using 6 of 32 coalitions, 6 new.
-- Iteration 2 -----------------------------------------------------------------
i Using 8 of 32 coalitions, 2 new.
-- Iteration 3 -----------------------------------------------------------------
i Using 12 of 32 coalitions, 4 new.
-- Iteration 4 -----------------------------------------------------------------
i Using 14 of 32 coalitions, 2 new.
-- Iteration 5 -----------------------------------------------------------------
i Using 16 of 32 coalitions, 2 new.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_groups = 32`, and is therefore set to `2^n_groups = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian
* Iterative estimation: TRUE
* Number of group-wise Shapley values: 5
* Number of observations to explain: 3
-- iterative computation started --
-- Iteration 1 -----------------------------------------------------------------
i Using 6 of 32 coalitions, 6 new.
-- Iteration 2 -----------------------------------------------------------------
i Using 8 of 32 coalitions, 2 new.
-- Iteration 3 -----------------------------------------------------------------
i Using 12 of 32 coalitions, 4 new.
-- Iteration 4 -----------------------------------------------------------------
i Using 14 of 32 coalitions, 2 new.
-- Iteration 5 -----------------------------------------------------------------
i Using 16 of 32 coalitions, 2 new.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: ctree
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: ctree
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
-- Explanation overview --
* Model class: <lm>
* Approach: ctree
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 10 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
-- Explanation overview --
* Model class: <lm>
* Approach: ctree
* Iterative estimation: FALSE
* Number of group-wise Shapley values: 3
* Number of observations to explain: 3
-- Main computation started --
i Using 6 of 8 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: ctree
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: ctree
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` at 2025-08-22 09:31:23 --------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
* Computations (temporary) saved at:
'D:\temp\2025_08_22_01_50_00_25364\Rtmp6z7oFl\shapr_obj_12b5461d2713b.rds'
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: independence, empirical, gaussian, and copula
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: independence, empirical, gaussian, and copula
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: independence, empirical, gaussian, and copula
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: gaussian, gaussian, gaussian, and gaussian
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: independence, empirical, independence, and empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: independence, empirical, independence, and empirical
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
-- Starting `shapr::explain()` -------------------------------------------------
i `max_n_coalitions` is `NULL` or larger than or `2^n_features = 32`, and is therefore set to `2^n_features = 32`.
-- Explanation overview --
* Model class: <lm>
* Approach: vaeac
* Iterative estimation: FALSE
* Number of feature-wise Shapley values: 5
* Number of observations to explain: 3
-- Main computation started --
i Using 32 of 32 coalitions.
Flavor: r-oldrel-windows-x86_64