Last updated on 2024-11-21 19:53:16 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| archivist | 13 | ||
| BetaBit | 13 | ||
| bgmm | 13 | ||
| breakDown | 13 | ||
| ceterisParibus | 3 | 6 | 4 |
| DALEX | 10 | 3 | |
| ddst | 10 | 3 | |
| drifter | 8 | 5 | |
| iBreakDown | 13 | ||
| ingredients | 13 | ||
| localModel | 13 | ||
| PBImisc | 13 | ||
| PogromcyDanych | 13 | ||
| proton | 13 | ||
| Przewodnik | 13 | ||
| SmarterPoland | 12 | 1 |
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: NOTE: 13
Version: 1.8.5
Check: Rd files
Result: NOTE
checkRd: (-1) bgmm-package.Rd:23: Escaped LaTeX specials: \&
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
Current CRAN status: OK: 13
Current CRAN status: ERROR: 3, NOTE: 6, OK: 4
Version: 0.4.2
Check: package subdirectories
Result: NOTE
Problems with news in ‘NEWS.md’:
Cannot extract version info from the following section titles:
Major refactoring of the code
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-windows-x86_64
Version: 0.4.2
Check: tests
Result: ERROR
Running ‘testthat.R’ [5s/5s]
Running the tests in ‘tests/testthat.R’ failed.
Complete output:
> library(testthat)
> library(ceterisParibus)
Loading required package: ggplot2
Loading required package: gower
>
> test_check("ceterisParibus")
Welcome to DALEX (version: 2.4.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
randomForest 4.7-1.2
Type rfNews() to see new features/changes/bug fixes.
Attaching package: 'randomForest'
The following object is masked from 'package:ggplot2':
margin
Preparation of a new explainer is initiated
-> model label : randomForest ( <1b>[33m default <1b>[39m )
-> data : 9000 rows 5 cols
-> target variable : 9000 values
-> predict function : yhat.randomForest will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package randomForest , ver. 4.7.1.2 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2010.982 , mean = 3505.971 , max = 5840.604
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -727.4451 , mean = 5.552194 , max = 1262.554
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : lm ( <1b>[33m default <1b>[39m )
-> data : 9000 rows 5 cols
-> target variable : 9000 values
-> predict function : yhat.lm will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package stats , ver. 4.5.0 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
y_hat new_x vname x_quant quant relative_quant
1001 4255.354 1920 construction.year 0.6268889 0.00 -0.6268889
1001.1 4300.702 1921 construction.year 0.6268889 0.01 -0.6168889
1001.2 4301.926 1922 construction.year 0.6268889 0.02 -0.6068889
1001.3 4305.352 1923 construction.year 0.6268889 0.03 -0.5968889
1001.4 4305.352 1923 construction.year 0.6268889 0.04 -0.5868889
1001.5 4267.723 1924 construction.year 0.6268889 0.05 -0.5768889
label
1001 randomForest
1001.1 randomForest
1001.2 randomForest
1001.3 randomForest
1001.4 randomForest
1001.5 randomForest
y_hat new_x vname x_quant quant relative_quant
1001 4255.354 1920 construction.year 0.6268889 0.00 -0.6268889
1001.1 4300.702 1921 construction.year 0.6268889 0.01 -0.6168889
1001.2 4301.926 1922 construction.year 0.6268889 0.02 -0.6068889
1001.3 4305.352 1923 construction.year 0.6268889 0.03 -0.5968889
1001.4 4305.352 1923 construction.year 0.6268889 0.04 -0.5868889
1001.5 4267.723 1924 construction.year 0.6268889 0.05 -0.5768889
label
1001 randomForest
1001.1 randomForest
1001.2 randomForest
1001.3 randomForest
1001.4 randomForest
1001.5 randomForest
y_hat new_x vname quant obs_id label
1001 4768.305 20 surface 0.00 0 randomForest
1001.1 4765.291 21 surface 0.01 0 randomForest
1001.2 4761.576 23 surface 0.02 0 randomForest
1001.3 4760.838 24 surface 0.03 0 randomForest
1001.4 4760.290 26 surface 0.04 0 randomForest
1001.5 4743.734 27 surface 0.05 0 randomForest
y_hat new_x vname quant obs_id label
1001 4768.305 20 surface 0.00 0 randomForest
1001.1 4765.291 21 surface 0.01 0 randomForest
1001.2 4761.576 23 surface 0.02 0 randomForest
1001.3 4760.838 24 surface 0.03 0 randomForest
1001.4 4760.290 26 surface 0.04 0 randomForest
1001.5 4743.734 27 surface 0.05 0 randomForest
Top profiles :
m2.price construction.year surface floor no.rooms district _yhat_
1958 4397 1920 20 3 2 Wola 4264.677
1958.1 4397 1921 20 3 2 Wola 4291.510
1958.2 4397 1922 20 3 2 Wola 4293.457
1958.3 4397 1923 20 3 2 Wola 4298.767
1958.4 4397 1923 20 3 2 Wola 4298.767
1958.5 4397 1924 20 3 2 Wola 4302.630
_vname_ _ids_ _label_
1958 construction.year 1958 randomForest
1958.1 construction.year 1958 randomForest
1958.2 construction.year 1958 randomForest
1958.3 construction.year 1958 randomForest
1958.4 construction.year 1958 randomForest
1958.5 construction.year 1958 randomForest
Top observations:
m2.price construction.year surface floor no.rooms district _yhat_ _y_
1958 4397 2005 20 3 2 Wola 4094.383 4397
_label_
1958 randomForest
m2.price construction.year surface floor no.rooms district _yhat_
1001 4644 1920 131 3 5 Srodmiescie 4255.354
1001.1 4644 1921 131 3 5 Srodmiescie 4300.702
1001.2 4644 1922 131 3 5 Srodmiescie 4301.926
1001.3 4644 1923 131 3 5 Srodmiescie 4305.352
1001.4 4644 1924 131 3 5 Srodmiescie 4267.723
1001.5 4644 1925 131 3 5 Srodmiescie 4264.109
_vname_ _ids_
1001 construction.year 1001
1001.1 construction.year 1001
1001.2 construction.year 1001
1001.3 construction.year 1001
1001.4 construction.year 1001
1001.5 construction.year 1001
m2.price construction.year surface floor no.rooms district _yhat_
1001 4644 1920 131 3 5 Srodmiescie 4255.354
1001.1 4644 1921 131 3 5 Srodmiescie 4300.702
1001.2 4644 1922 131 3 5 Srodmiescie 4301.926
1001.3 4644 1923 131 3 5 Srodmiescie 4305.352
1001.4 4644 1924 131 3 5 Srodmiescie 4267.723
1001.5 4644 1925 131 3 5 Srodmiescie 4264.109
_vname_ _ids_
1001 construction.year 1001
1001.1 construction.year 1001
1001.2 construction.year 1001
1001.3 construction.year 1001
1001.4 construction.year 1001
1001.5 construction.year 1001
[ FAIL 1 | WARN 3 | SKIP 0 | PASS 29 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_plot_interactive_what_if.R:8:3'): output ───────────────────────
<defunctError/error/condition>
Error in `ggiraph::ggiraph(code = print(pl), hover_css = "fill-opacity:.3;cursor:pointer;")`: 'ggiraph' is defunct.
Use 'girafe' instead.
See help("Defunct")
Backtrace:
▆
1. ├─testthat::expect_is(plot_interactive(wi_rf_all), "ggiraph") at test_plot_interactive_what_if.R:8:3
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. ├─ceterisParibus::plot_interactive(wi_rf_all)
5. └─ceterisParibus:::plot_interactive.what_if_explainer(wi_rf_all)
6. └─ggiraph::ggiraph(code = print(pl), hover_css = "fill-opacity:.3;cursor:pointer;")
7. └─base::.Defunct(new = "girafe")
[ FAIL 1 | WARN 3 | SKIP 0 | PASS 29 ]
Error: Test failures
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 0.4.2
Check: tests
Result: ERROR
Running 'testthat.R' [5s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(ceterisParibus)
Loading required package: ggplot2
Loading required package: gower
>
> test_check("ceterisParibus")
Welcome to DALEX (version: 2.4.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
randomForest 4.7-1.2
Type rfNews() to see new features/changes/bug fixes.
Attaching package: 'randomForest'
The following object is masked from 'package:ggplot2':
margin
Preparation of a new explainer is initiated
-> model label : randomForest ( <1b>[33m default <1b>[39m )
-> data : 9000 rows 5 cols
-> target variable : 9000 values
-> predict function : yhat.randomForest will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package randomForest , ver. 4.7.1.2 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2010.982 , mean = 3505.971 , max = 5840.604
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -727.4451 , mean = 5.552194 , max = 1262.554
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : lm ( <1b>[33m default <1b>[39m )
-> data : 9000 rows 5 cols
-> target variable : 9000 values
-> predict function : yhat.lm will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package stats , ver. 4.5.0 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
y_hat new_x vname x_quant quant relative_quant
1001 4255.354 1920 construction.year 0.6268889 0.00 -0.6268889
1001.1 4300.702 1921 construction.year 0.6268889 0.01 -0.6168889
1001.2 4301.926 1922 construction.year 0.6268889 0.02 -0.6068889
1001.3 4305.352 1923 construction.year 0.6268889 0.03 -0.5968889
1001.4 4305.352 1923 construction.year 0.6268889 0.04 -0.5868889
1001.5 4267.723 1924 construction.year 0.6268889 0.05 -0.5768889
label
1001 randomForest
1001.1 randomForest
1001.2 randomForest
1001.3 randomForest
1001.4 randomForest
1001.5 randomForest
y_hat new_x vname x_quant quant relative_quant
1001 4255.354 1920 construction.year 0.6268889 0.00 -0.6268889
1001.1 4300.702 1921 construction.year 0.6268889 0.01 -0.6168889
1001.2 4301.926 1922 construction.year 0.6268889 0.02 -0.6068889
1001.3 4305.352 1923 construction.year 0.6268889 0.03 -0.5968889
1001.4 4305.352 1923 construction.year 0.6268889 0.04 -0.5868889
1001.5 4267.723 1924 construction.year 0.6268889 0.05 -0.5768889
label
1001 randomForest
1001.1 randomForest
1001.2 randomForest
1001.3 randomForest
1001.4 randomForest
1001.5 randomForest
y_hat new_x vname quant obs_id label
1001 4768.305 20 surface 0.00 0 randomForest
1001.1 4765.291 21 surface 0.01 0 randomForest
1001.2 4761.576 23 surface 0.02 0 randomForest
1001.3 4760.838 24 surface 0.03 0 randomForest
1001.4 4760.290 26 surface 0.04 0 randomForest
1001.5 4743.734 27 surface 0.05 0 randomForest
y_hat new_x vname quant obs_id label
1001 4768.305 20 surface 0.00 0 randomForest
1001.1 4765.291 21 surface 0.01 0 randomForest
1001.2 4761.576 23 surface 0.02 0 randomForest
1001.3 4760.838 24 surface 0.03 0 randomForest
1001.4 4760.290 26 surface 0.04 0 randomForest
1001.5 4743.734 27 surface 0.05 0 randomForest
Top profiles :
m2.price construction.year surface floor no.rooms district _yhat_
1958 4397 1920 20 3 2 Wola 4264.677
1958.1 4397 1921 20 3 2 Wola 4291.510
1958.2 4397 1922 20 3 2 Wola 4293.457
1958.3 4397 1923 20 3 2 Wola 4298.767
1958.4 4397 1923 20 3 2 Wola 4298.767
1958.5 4397 1924 20 3 2 Wola 4302.630
_vname_ _ids_ _label_
1958 construction.year 1958 randomForest
1958.1 construction.year 1958 randomForest
1958.2 construction.year 1958 randomForest
1958.3 construction.year 1958 randomForest
1958.4 construction.year 1958 randomForest
1958.5 construction.year 1958 randomForest
Top observations:
m2.price construction.year surface floor no.rooms district _yhat_ _y_
1958 4397 2005 20 3 2 Wola 4094.383 4397
_label_
1958 randomForest
m2.price construction.year surface floor no.rooms district _yhat_
1001 4644 1920 131 3 5 Srodmiescie 4255.354
1001.1 4644 1921 131 3 5 Srodmiescie 4300.702
1001.2 4644 1922 131 3 5 Srodmiescie 4301.926
1001.3 4644 1923 131 3 5 Srodmiescie 4305.352
1001.4 4644 1924 131 3 5 Srodmiescie 4267.723
1001.5 4644 1925 131 3 5 Srodmiescie 4264.109
_vname_ _ids_
1001 construction.year 1001
1001.1 construction.year 1001
1001.2 construction.year 1001
1001.3 construction.year 1001
1001.4 construction.year 1001
1001.5 construction.year 1001
m2.price construction.year surface floor no.rooms district _yhat_
1001 4644 1920 131 3 5 Srodmiescie 4255.354
1001.1 4644 1921 131 3 5 Srodmiescie 4300.702
1001.2 4644 1922 131 3 5 Srodmiescie 4301.926
1001.3 4644 1923 131 3 5 Srodmiescie 4305.352
1001.4 4644 1924 131 3 5 Srodmiescie 4267.723
1001.5 4644 1925 131 3 5 Srodmiescie 4264.109
_vname_ _ids_
1001 construction.year 1001
1001.1 construction.year 1001
1001.2 construction.year 1001
1001.3 construction.year 1001
1001.4 construction.year 1001
1001.5 construction.year 1001
[ FAIL 1 | WARN 3 | SKIP 0 | PASS 29 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_plot_interactive_what_if.R:8:3'): output ───────────────────────
<defunctError/error/condition>
Error in `ggiraph::ggiraph(code = print(pl), hover_css = "fill-opacity:.3;cursor:pointer;")`: 'ggiraph' is defunct.
Use 'girafe' instead.
See help("Defunct")
Backtrace:
▆
1. ├─testthat::expect_is(plot_interactive(wi_rf_all), "ggiraph") at test_plot_interactive_what_if.R:8:3
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. ├─ceterisParibus::plot_interactive(wi_rf_all)
5. └─ceterisParibus:::plot_interactive.what_if_explainer(wi_rf_all)
6. └─ggiraph::ggiraph(code = print(pl), hover_css = "fill-opacity:.3;cursor:pointer;")
7. └─base::.Defunct(new = "girafe")
[ FAIL 1 | WARN 3 | SKIP 0 | PASS 29 ]
Error: Test failures
Execution halted
Flavor: r-devel-windows-x86_64
Version: 0.4.2
Check: LazyData
Result: NOTE
'LazyData' is specified without a 'data' directory
Flavors: r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-windows-x86_64
Version: 0.4.2
Check: tests
Result: ERROR
Running 'testthat.R' [7s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
> library(testthat)
> library(ceterisParibus)
Loading required package: ggplot2
Loading required package: gower
>
> test_check("ceterisParibus")
Welcome to DALEX (version: 2.4.3).
Find examples and detailed introduction at: http://ema.drwhy.ai/
Additional features will be available after installation of: ggpubr.
Use 'install_dependencies()' to get all suggested dependencies
randomForest 4.7-1.2
Type rfNews() to see new features/changes/bug fixes.
Attaching package: 'randomForest'
The following object is masked from 'package:ggplot2':
margin
Preparation of a new explainer is initiated
-> model label : randomForest ( <1b>[33m default <1b>[39m )
-> data : 9000 rows 5 cols
-> target variable : 9000 values
-> predict function : yhat.randomForest will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package randomForest , ver. 4.7.1.2 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 2010.982 , mean = 3505.971 , max = 5840.604
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -727.4451 , mean = 5.552194 , max = 1262.554
<1b>[32m A new explainer has been created! <1b>[39m
Preparation of a new explainer is initiated
-> model label : lm ( <1b>[33m default <1b>[39m )
-> data : 9000 rows 5 cols
-> target variable : 9000 values
-> predict function : yhat.lm will be used ( <1b>[33m default <1b>[39m )
-> predicted values : No value for predict function target column. ( <1b>[33m default <1b>[39m )
-> model_info : package stats , ver. 4.3.3 , task regression ( <1b>[33m default <1b>[39m )
-> predicted values : numerical, min = 1792.597 , mean = 3506.836 , max = 6241.447
-> residual function : difference between y and yhat ( <1b>[33m default <1b>[39m )
-> residuals : numerical, min = -257.2555 , mean = 4.687686 , max = 472.356
<1b>[32m A new explainer has been created! <1b>[39m
y_hat new_x vname x_quant quant relative_quant
1001 4255.354 1920 construction.year 0.6268889 0.00 -0.6268889
1001.1 4300.702 1921 construction.year 0.6268889 0.01 -0.6168889
1001.2 4301.926 1922 construction.year 0.6268889 0.02 -0.6068889
1001.3 4305.352 1923 construction.year 0.6268889 0.03 -0.5968889
1001.4 4305.352 1923 construction.year 0.6268889 0.04 -0.5868889
1001.5 4267.723 1924 construction.year 0.6268889 0.05 -0.5768889
label
1001 randomForest
1001.1 randomForest
1001.2 randomForest
1001.3 randomForest
1001.4 randomForest
1001.5 randomForest
y_hat new_x vname x_quant quant relative_quant
1001 4255.354 1920 construction.year 0.6268889 0.00 -0.6268889
1001.1 4300.702 1921 construction.year 0.6268889 0.01 -0.6168889
1001.2 4301.926 1922 construction.year 0.6268889 0.02 -0.6068889
1001.3 4305.352 1923 construction.year 0.6268889 0.03 -0.5968889
1001.4 4305.352 1923 construction.year 0.6268889 0.04 -0.5868889
1001.5 4267.723 1924 construction.year 0.6268889 0.05 -0.5768889
label
1001 randomForest
1001.1 randomForest
1001.2 randomForest
1001.3 randomForest
1001.4 randomForest
1001.5 randomForest
y_hat new_x vname quant obs_id label
1001 4768.305 20 surface 0.00 0 randomForest
1001.1 4765.291 21 surface 0.01 0 randomForest
1001.2 4761.576 23 surface 0.02 0 randomForest
1001.3 4760.838 24 surface 0.03 0 randomForest
1001.4 4760.290 26 surface 0.04 0 randomForest
1001.5 4743.734 27 surface 0.05 0 randomForest
y_hat new_x vname quant obs_id label
1001 4768.305 20 surface 0.00 0 randomForest
1001.1 4765.291 21 surface 0.01 0 randomForest
1001.2 4761.576 23 surface 0.02 0 randomForest
1001.3 4760.838 24 surface 0.03 0 randomForest
1001.4 4760.290 26 surface 0.04 0 randomForest
1001.5 4743.734 27 surface 0.05 0 randomForest
Top profiles :
m2.price construction.year surface floor no.rooms district _yhat_
1958 4397 1920 20 3 2 Wola 4264.677
1958.1 4397 1921 20 3 2 Wola 4291.510
1958.2 4397 1922 20 3 2 Wola 4293.457
1958.3 4397 1923 20 3 2 Wola 4298.767
1958.4 4397 1923 20 3 2 Wola 4298.767
1958.5 4397 1924 20 3 2 Wola 4302.630
_vname_ _ids_ _label_
1958 construction.year 1958 randomForest
1958.1 construction.year 1958 randomForest
1958.2 construction.year 1958 randomForest
1958.3 construction.year 1958 randomForest
1958.4 construction.year 1958 randomForest
1958.5 construction.year 1958 randomForest
Top observations:
m2.price construction.year surface floor no.rooms district _yhat_ _y_
1958 4397 2005 20 3 2 Wola 4094.383 4397
_label_
1958 randomForest
m2.price construction.year surface floor no.rooms district _yhat_
1001 4644 1920 131 3 5 Srodmiescie 4255.354
1001.1 4644 1921 131 3 5 Srodmiescie 4300.702
1001.2 4644 1922 131 3 5 Srodmiescie 4301.926
1001.3 4644 1923 131 3 5 Srodmiescie 4305.352
1001.4 4644 1924 131 3 5 Srodmiescie 4267.723
1001.5 4644 1925 131 3 5 Srodmiescie 4264.109
_vname_ _ids_
1001 construction.year 1001
1001.1 construction.year 1001
1001.2 construction.year 1001
1001.3 construction.year 1001
1001.4 construction.year 1001
1001.5 construction.year 1001
m2.price construction.year surface floor no.rooms district _yhat_
1001 4644 1920 131 3 5 Srodmiescie 4255.354
1001.1 4644 1921 131 3 5 Srodmiescie 4300.702
1001.2 4644 1922 131 3 5 Srodmiescie 4301.926
1001.3 4644 1923 131 3 5 Srodmiescie 4305.352
1001.4 4644 1924 131 3 5 Srodmiescie 4267.723
1001.5 4644 1925 131 3 5 Srodmiescie 4264.109
_vname_ _ids_
1001 construction.year 1001
1001.1 construction.year 1001
1001.2 construction.year 1001
1001.3 construction.year 1001
1001.4 construction.year 1001
1001.5 construction.year 1001
[ FAIL 1 | WARN 3 | SKIP 0 | PASS 29 ]
══ Failed tests ════════════════════════════════════════════════════════════════
── Error ('test_plot_interactive_what_if.R:8:3'): output ───────────────────────
<defunctError/error/condition>
Error: 'ggiraph' is defunct.
Use 'girafe' instead.
See help("Defunct")
Backtrace:
▆
1. ├─testthat::expect_is(plot_interactive(wi_rf_all), "ggiraph") at test_plot_interactive_what_if.R:8:3
2. │ └─testthat::quasi_label(enquo(object), label, arg = "object")
3. │ └─rlang::eval_bare(expr, quo_get_env(quo))
4. ├─ceterisParibus::plot_interactive(wi_rf_all)
5. └─ceterisParibus:::plot_interactive.what_if_explainer(wi_rf_all)
6. └─ggiraph::ggiraph(code = print(pl), hover_css = "fill-opacity:.3;cursor:pointer;")
7. └─base::.Defunct(new = "girafe")
[ FAIL 1 | WARN 3 | SKIP 0 | PASS 29 ]
Error: Test failures
Execution halted
Flavor: r-oldrel-windows-x86_64
Current CRAN status: NOTE: 10, OK: 3
Version: 2.4.3
Check: Rd files
Result: NOTE
checkRd: (-1) plot.model_parts.Rd:25: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.model_parts.Rd:26: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.model_parts.Rd:27: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.model_parts.Rd:28: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.model_parts.Rd:29: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.model_parts.Rd:30-31: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.model_profile.Rd:21-22: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.model_profile.Rd:23: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.model_profile.Rd:24: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.model_profile.Rd:25: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.model_profile.Rd:26: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.model_profile.Rd:27: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.model_profile.Rd:28: Lost braces in \itemize; \value handles \item{}{} directly
checkRd: (-1) plot.predict_parts.Rd:25: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:26-27: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:28: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:29: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:30: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:31: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:32: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:33: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:34-35: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:36: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:37: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:38-39: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:40: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:45: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:46: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:47: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:48: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_parts.Rd:53: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:25: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:26: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:27: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:28: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:29: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:30-31: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:32: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:33-34: Lost braces in \itemize; meant \describe ?
checkRd: (-1) plot.predict_profile.Rd:35: Lost braces in \itemize; meant \describe ?
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
Version: 2.4.3
Check: Rd cross-references
Result: NOTE
Found the following Rd file(s) with Rd \link{} targets missing package
anchors:
plot.predict_parts.Rd: break_down, local_attributions,
local_interactions
Please provide package anchors for all Rd \link{} targets not in the
package itself and the base packages.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-windows-x86_64
Current CRAN status: NOTE: 10, OK: 3
Version: 1.4
Check: Rd files
Result: NOTE
checkRd: (-1) ddst-package.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$W_k=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1}[1/sqrt(n) sum_{i=1}^n l(Z_i)]'$},
| ^
checkRd: (-1) ddst-package.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$W_k=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1}[1/sqrt(n) sum_{i=1}^n l(Z_i)]'$},
| ^
checkRd: (-1) ddst-package.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$W_k=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1}[1/sqrt(n) sum_{i=1}^n l(Z_i)]'$},
| ^
checkRd: (-1) ddst-package.Rd:31: Lost braces; missing escapes or markup?
31 | where \emph{$l(Z_i)$}, i=1,...,n, is \emph{k}-dimensional (row) score vector, the symbol \emph{'} denotes transposition while \emph{$I=Cov_{theta_0}[l(Z_1)]'[l(Z_1)]$}. Following Neyman's idea of modelling underlying distributions one gets \emph{$l(Z_i)=(phi_1(F(Z_i)),...,phi_k(F(Z_i)))$} and \emph{I} being the identity matrix, where \emph{$phi_j$}'s, j >= 1, are zero mean orthonormal functions on [0,1], while \emph{F} is the completely specified null distribution function.
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:35: Lost braces; missing escapes or markup?
35 | \emph{$W_k^{*}(tilde gamma)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)][I^*(tilde gamma)]^{-1}[1/sqrt(n) sum_{i=1}^n l^*(Z_i;tilde gamma)]'$},
| ^
checkRd: (-1) ddst-package.Rd:36: Lost braces; missing escapes or markup?
36 | where \emph{$tilde gamma$} is an appropriate estimator of \emph{$gamma$} while \emph{$I^*(gamma)=Cov_{theta_0}[l^*(Z_1;gamma)]'[l^*(Z_1;gamma)]$}. More details can be found in Janic and Ledwina (2008), Kallenberg and Ledwina (1997 a,b) as well as Inglot and Ledwina (2006 a,b).
| ^
checkRd: (-1) ddst-package.Rd:40: Lost braces
40 | \emph{$T = min{1 <= k <= d: W_k-pi(k,n,c) >= W_j-pi(j,n,c), j=1,...,d}$}
| ^
checkRd: (-1) ddst-package.Rd:45: Lost braces
45 | $T^* = min{1 <= k <= d: W_k^*(tilde gamma)-pi^*(k,n,c) >= W_j^*(tilde gamma)-pi^*(j,n,c), j=1,...,d}$}.
| ^
checkRd: (-1) ddst-package.Rd:49: Lost braces
49 | \emph{$pi(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k| <= sqrt(c log(n)), 2j, if max{1 <= k <= d}|Y_k|>sqrt(c log(n)). }$}
| ^
checkRd: (-1) ddst-package.Rd:49: Lost braces
49 | \emph{$pi(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k| <= sqrt(c log(n)), 2j, if max{1 <= k <= d}|Y_k|>sqrt(c log(n)). }$}
| ^
checkRd: (-1) ddst-package.Rd:49: Lost braces
49 | \emph{$pi(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k| <= sqrt(c log(n)), 2j, if max{1 <= k <= d}|Y_k|>sqrt(c log(n)). }$}
| ^
checkRd: (-1) ddst-package.Rd:54: Lost braces
54 | $pi^*(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k^*| <= sqrt(c log(n)),2j if max(1 <= k <= d)|Y_k^*| > sqrt(c log(n))}$}.
| ^
checkRd: (-1) ddst-package.Rd:54: Lost braces
54 | $pi^*(j,n,c)={jlog n, if max{1 <= k <= d}|Y_k^*| <= sqrt(c log(n)),2j if max(1 <= k <= d)|Y_k^*| > sqrt(c log(n))}$}.
| ^
checkRd: (-1) ddst-package.Rd:58: Lost braces; missing escapes or markup?
58 | \emph{$(Y_1,...,Y_k)=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1/2}$}
| ^
checkRd: (-1) ddst-package.Rd:58: Lost braces; missing escapes or markup?
58 | \emph{$(Y_1,...,Y_k)=[1/sqrt(n) sum_{i=1}^n l(Z_i)]I^{-1/2}$}
| ^
checkRd: (-1) ddst-package.Rd:62: Lost braces; missing escapes or markup?
62 | \emph{$(Y_1^*,...,Y_k^*)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i; tilde gamma)][I^*(tilde gamma)]^{-1/2}$}.
| ^
checkRd: (-1) ddst-package.Rd:62: Lost braces; missing escapes or markup?
62 | \emph{$(Y_1^*,...,Y_k^*)=[1/sqrt(n) sum_{i=1}^n l^*(Z_i; tilde gamma)][I^*(tilde gamma)]^{-1/2}$}.
| ^
checkRd: (-1) ddst-package.Rd:65: Lost braces; missing escapes or markup?
65 | and \emph{$W_{T^*} = W_{T^*}(tilde gamma)$}, respectively. For details see Inglot and Ledwina (2006 a,b,c).
| ^
checkRd: (-1) ddst-package.Rd:65: Lost braces; missing escapes or markup?
65 | and \emph{$W_{T^*} = W_{T^*}(tilde gamma)$}, respectively. For details see Inglot and Ledwina (2006 a,b,c).
| ^
checkRd: (-1) ddst-package.Rd:67: Lost braces; missing escapes or markup?
67 | The choice of \emph{c} in \emph{T} and \emph{$T^*$} is decisive to finite sample behaviour of the selection rules and pertaining statistics \emph{$W_T$} and \emph{$W_{T^*}(tilde gamma)$}. In particular, under large \emph{c}'s the rules behave similarly as Schwarz's (1978) BIC while for \emph{c=0} they mimic Akaike's (1973) AIC. For moderate sample sizes, values \emph{c in (2,2.5)} guarantee, under `smooth' departures, only slightly smaller power as in case BIC were used and simultaneously give much higher power than BIC under multimodal alternatives. In genral, large \emph{c's} are recommended if changes in location, scale, skewness and kurtosis are in principle aimed to be detected. For evidence and discussion see Inglot and Ledwina (2006 c).
| ^
checkRd: (-1) ddst-package.Rd:69: Lost braces; missing escapes or markup?
69 | It \emph{c>0} then the limiting null distribution of \emph{$W_T$} and \emph{$W_{T^*}(tilde gamma)$} is central chi-squared with one degree of freedom. In our implementation, for given \emph{n}, both critical values and \emph{p}-values are computed by MC method.
| ^
checkRd: (-1) ddst-package.Rd:71: Lost braces; missing escapes or markup?
71 | Empirical distributions of \emph{T} and \emph{$T^*$} as well as \emph{$W_T$} and \emph{$W_{T^*}(tilde gamma)$} are not essentially influenced by the choice of reasonably large \emph{d}'s, provided that sample size is at least moderate.
| ^
checkRd: (-1) ddst.exp.test.Rd:27: Lost braces; missing escapes or markup?
27 | Modelling alternatives similarly as in Kallenberg and Ledwina (1997 a,b), e.g., and estimating \emph{$gamma$} by \emph{$tilde gamma= 1/n sum_{i=1}^n Z_i$} yields the efficient score
| ^
checkRd: (-1) ddst.exp.test.Rd:30: Lost braces; missing escapes or markup?
30 | The matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and computed in a numerical way in case of cosine basis. In the implementation the default value of \emph{c} in \emph{$T^*$} is set to be 100.
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:29: Lost braces; missing escapes or markup?
29 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=-1/n sum_{i=1}^n Z_i + varepsilon G$}, where \emph{$varepsilon approx 0.577216 $} is the Euler constant and \emph{$ G = tilde gamma_2 = [n(n-1) ln2]^{-1}sum_{1<= j < i <= n}(Z_{n:i}^o - Z_{n:j}^o) $} while \emph{$Z_{n:1}^o <= ... <= Z_{n:n}^o$}
| ^
checkRd: (-1) ddst.extr.test.Rd:33: Lost braces; missing escapes or markup?
33 | The related matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and numerical methods for cosine functions. In the implementation the default value of \emph{c} in \emph{$T^*$} was fixed to be 100. Hence, \emph{$T^*$} is Schwarz-type model selection rule. The resulting data driven test statistic for extreme value distribution is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.extr.test.Rd:33: Lost braces; missing escapes or markup?
33 | The related matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and numerical methods for cosine functions. In the implementation the default value of \emph{c} in \emph{$T^*$} was fixed to be 100. Hence, \emph{$T^*$} is Schwarz-type model selection rule. The resulting data driven test statistic for extreme value distribution is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.extr.test.Rd:33: Lost braces; missing escapes or markup?
33 | The related matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and numerical methods for cosine functions. In the implementation the default value of \emph{c} in \emph{$T^*$} was fixed to be 100. Hence, \emph{$T^*$} is Schwarz-type model selection rule. The resulting data driven test statistic for extreme value distribution is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.norm.test.Rd:30: Lost braces; missing escapes or markup?
30 | \emph{$gamma=(gamma_1,gamma_2)$} is estimated by \emph{$tilde gamma=(tilde gamma_1,tilde gamma_2)$}, where \emph{$tilde gamma_1=1/n sum_{i=1}^n Z_i$} and
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:31: Lost braces; missing escapes or markup?
31 | \emph{$tilde gamma_2 = 1/(n-1) sum_{i=1}^{n-1}(Z_{n:i+1}-Z_{n:i})(H_{i+1}-H_i)$},
| ^
checkRd: (-1) ddst.norm.test.Rd:32: Lost braces; missing escapes or markup?
32 | while \emph{$Z_{n:1}<= ... <= Z_{n:n}$} are ordered values of \emph{$Z_1, ..., Z_n$} and \emph{$H_i= phi^{-1}((i-3/8)(n+1/4))$}, cf. Chen and Shapiro (1995).
| ^
checkRd: (-1) ddst.norm.test.Rd:32: Lost braces; missing escapes or markup?
32 | while \emph{$Z_{n:1}<= ... <= Z_{n:n}$} are ordered values of \emph{$Z_1, ..., Z_n$} and \emph{$H_i= phi^{-1}((i-3/8)(n+1/4))$}, cf. Chen and Shapiro (1995).
| ^
checkRd: (-1) ddst.norm.test.Rd:32: Lost braces; missing escapes or markup?
32 | while \emph{$Z_{n:1}<= ... <= Z_{n:n}$} are ordered values of \emph{$Z_1, ..., Z_n$} and \emph{$H_i= phi^{-1}((i-3/8)(n+1/4))$}, cf. Chen and Shapiro (1995).
| ^
checkRd: (-1) ddst.norm.test.Rd:35: Lost braces; missing escapes or markup?
35 | The pertaining matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and is computed in a numerical way in case of cosine basis. In the implementation of \emph{$T^*$} the default value of \emph{c} is set to be 100. Therefore, in practice, \emph{$T^*$} is Schwarz-type criterion. See Inglot and Ledwina (2006) as well as Janic and Ledwina (2008) for comments. The resulting data driven test statistic for normality is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.norm.test.Rd:35: Lost braces; missing escapes or markup?
35 | The pertaining matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and is computed in a numerical way in case of cosine basis. In the implementation of \emph{$T^*$} the default value of \emph{c} is set to be 100. Therefore, in practice, \emph{$T^*$} is Schwarz-type criterion. See Inglot and Ledwina (2006) as well as Janic and Ledwina (2008) for comments. The resulting data driven test statistic for normality is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.norm.test.Rd:35: Lost braces; missing escapes or markup?
35 | The pertaining matrix \emph{$[I^*(tilde gamma)]^{-1}$} does not depend on \emph{$tilde gamma$} and is calculated for succeding dimensions \emph{k} using some recurrent relations for Legendre's polynomials and is computed in a numerical way in case of cosine basis. In the implementation of \emph{$T^*$} the default value of \emph{c} is set to be 100. Therefore, in practice, \emph{$T^*$} is Schwarz-type criterion. See Inglot and Ledwina (2006) as well as Janic and Ledwina (2008) for comments. The resulting data driven test statistic for normality is \emph{$W_{T^*}=W_{T^*}(tilde gamma)$}.
| ^
checkRd: (-1) ddst.uniform.test.Rd:25: Lost braces; missing escapes or markup?
25 | $W_k=[1/sqrt(n) sum_{j=1}^k sum_{i=1}^n phi_j(Z_i)]^2$},
| ^
checkRd: (-1) ddst.uniform.test.Rd:25: Lost braces; missing escapes or markup?
25 | $W_k=[1/sqrt(n) sum_{j=1}^k sum_{i=1}^n phi_j(Z_i)]^2$},
| ^
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
Current CRAN status: NOTE: 8, OK: 5
Version: 0.2.1
Check: LazyData
Result: NOTE
'LazyData' is specified without a 'data' directory
Flavors: 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
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: NOTE: 12, OK: 1
Version: 1.8.1
Check: Rd files
Result: NOTE
checkRd: (-1) cities_lon_lat.Rd:6: Lost braces
6 | A subset of world.cities{maps}. Extracted in order to shink number of dependencies.
| ^
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
Version: 1.8.1
Check: installed package size
Result: NOTE
installed size is 5.3Mb
sub-directories of 1Mb or more:
data 5.1Mb
Flavors: r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.