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Type 'q()' to quit R. > # 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(adm) > > test_check("adm") 1 rows were excluded from database because NAs were found Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Predicting an individual model Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Predicting an individual model Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Predicting an individual model Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 Using 100 trees... -- Partition number 2/3 Using 100 trees... -- Partition number 3/3 Using 100 trees... Predicting an individual model Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + I(bio12^2) + I(elevation^2) + I(sand^2) + I(bio12^3) + I(elevation^3) + I(sand^3) + bio12:elevation + bio12:sand + elevation:sand + bio12:elevation:sand Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Predicting an individual model Formula used for model fitting: ind_ha ~ pb(bio12) + pb(elevation) + pb(sand) + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Predicting an individual model Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Predicting an individual model Loading required package: gamlss Loading required package: splines Loading required package: gamlss.data Attaching package: 'gamlss.data' The following object is masked from 'package:datasets': sleep Loading required package: gamlss.dist Loading required package: nlme Attaching package: 'nlme' The following object is masked from 'package:dplyr': collapse Loading required package: parallel ********** GAMLSS Version 5.5-5 ********** For more on GAMLSS look at https://www.gamlss.com/ Type gamlssNews() to see new features/changes/bug fixes. Formula used for model fitting: ind_ha ~ pb(elevation) + pb(sand) + pb(bio3) + pb(bio12) Replica number: 1/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 2/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 3/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ elevation + sand + bio3 + bio12 Replica number: 1/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 2/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 3/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 1/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 2/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 3/3 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco + I(bio12^2) + I(elevation^2) + I(sand^2) + I(bio12^3) + I(elevation^3) + I(sand^3) Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 Using 100 trees... -- Partition number 2/3 Using 100 trees... -- Partition number 3/3 Using 100 trees... Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ bio12 + elevation + sand + eco Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 Formula used for model fitting: ind_ha ~ pb(bio12) + pb(elevation) + pb(sand) Formula used for model fitting: ind_ha ~ pb(bio12) + pb(elevation) + pb(sand) Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting a list of models Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Predicting an individual model Response variable is continuous and need to be transformed to integer in order to test for discrete families. Selected 29 suitable families for the data. Response variable is continuous and need to be transformed to integer in order to test for discrete families. Selected 29 suitable families for the data. Using provided grid. Searching for optimal hyperparameters... Fitting the best model... Replica number: 1/1 -- Partition number 1/3 -- Partition number 2/3 -- Partition number 3/3 The best model was achieved with: max_depth = 8 learning_rate = 0.2 min_split_loss = 1 colsample_bytree = 0.5 min_child_weight = 1 subsample = 1 nrounds = 100 [ FAIL 0 | WARN 0 | SKIP 28 | PASS 369 ] ══ Skipped tests (28) ══════════════════════════════════════════════════════════ • On CRAN (19): 'test-adm_predict.R:218:3', 'test-adm_predict.R:290:3', 'test-data_abund_bpdp.R:163:3', 'test-fit_torch.R:35:3', 'test-tune_abund_cnn.R:17:3', 'test-tune_abund_cnn.R:147:3', 'test-tune_abund_dnn.R:19:3', 'test-tune_abund_gam.R:20:3', 'test-tune_abund_gam.R:74:3', 'test-tune_abund_gbm.R:15:3', 'test-tune_abund_gbm.R:69:3', 'test-tune_abund_glm.R:21:3', 'test-tune_abund_glm.R:70:3', 'test-tune_abund_net.R:12:3', 'test-tune_abund_net.R:60:3', 'test-tune_abund_raf.R:16:3', 'test-tune_abund_raf.R:64:3', 'test-tune_abund_svm.R:13:3', 'test-tune_abund_svm.R:65:3' • Skipping (5): 'test-generate_arch_list.R:6:5', 'test-generate_arch_list.R:28:5', 'test-select_arch_list.R:3:3', 'test-tune_abund_cnn.R:76:5', 'test-tune_abund_dnn.R:62:5' • torch::torch_is_installed() is not TRUE (4): 'test-fit_torch.R:6:3', 'test-fit_torch.R:17:3', 'test-generate_architecture.R:2:3', 'test-generate_architecture.R:9:3' [ FAIL 0 | WARN 0 | SKIP 28 | PASS 369 ] > > proc.time() user system elapsed 110.51 10.64 146.32