R Under development (unstable) (2024-07-20 r86909 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. 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/tests.html > # * https://testthat.r-lib.org/reference/test_package.html#special-files > > library(testthat) > library(tenm) > > test_check("tenm") Attaching package: 'purrr' The following object is masked from 'package:testthat': is_null ***************************************************************** Here is a list of variables that can summarize your niche information, according to the threshold of 0.5 : temperature precip ***************************************************************** ---------------------------------------------------------------- Correlation list: Variable temperature is strongly correlated with: temperature 1 ---------------------------------------------------------------- Variable precip is strongly correlated with: precip 1 ---------------------------------------------------------------- ***************************************************************** Here is a list of variables that can summarize your niche information, according to the threshold of 0.5 : temperature precip ***************************************************************** ---------------------------------------------------------------- Correlation list: Variable temperature is strongly correlated with: temperature 1 ---------------------------------------------------------------- Variable precip is strongly correlated with: precip 1 ---------------------------------------------------------------- Progress: 100% Progress: 100% Progress: 100% Progress: 100% Progress: 100% Progress: 100% Progress: 100% Progress: 100% Progress: 100% Progress: ── 100% Progress: ──────── 100% Progress: ──────────────── 100% Progress: ──────────────────────── 100% Progress: ─────────────────────────────── 100% Progress: 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Progress: ─────────────────────────────────────────────────────────── 100% Progress: ──────────────────────────────────────────────────────────── 100% Progress: ──────────────────────────────────────────────────────────── 100% Progress: ───────────────────────────────────────────────────────────── 100% Progress: ───────────────────────────────────────────────────────────── 100% Progress: ────────────────────────────────────────────────────────────── 100% Progress: ─────────────────────────────────────────────────────────────── 100% Progress: ─────────────────────────────────────────────────────────────── 100%------------------------------------------------------------------- **** Starting model selection process **** ------------------------------------------------------------------- A total number of 84 models will be created for combinations of 9 variables taken by 3 ------------------------------------------------------------------- **A total number of 84 models will be tested ** ------------------------------------------------------------------- 54 models passed omr_criteria for train data 9 models passed omr_criteria for test data 9 models passed omr_criteria for train and test data ------------------------------------------------------------------- **** Starting model selection process **** ------------------------------------------------------------------- A total number of 84 models will be created for combinations of 9 variables taken by 3 ------------------------------------------------------------------- **A total number of 84 models will be tested ** ------------------------------------------------------------------- 54 models passed omr_criteria for train data 9 models passed omr_criteria for test data 9 models passed omr_criteria for train and test data ------------------------------------------------------------------- **** Starting model selection process **** ------------------------------------------------------------------- A total number of 84 models will be created for combinations of 9 variables taken by 3 A total number of 126 models will be created for combinations of 9 variables taken by 4 ------------------------------------------------------------------- **A total number of 210 models will be tested ** ------------------------------------------------------------------- Doing calibration from model 1 to 100 in process 1 Doing calibration from model 101 to 200 in process 2 Doing calibration from model 201 to 210 in process 3 Finishing calibration of models 1 to 100 Finishing calibration of models 101 to 200 Finishing calibration of models 201 to 210 Finishing... ------------------------------------------------------------------- 124 models passed omr_criteria for train data 19 models passed omr_criteria for test data 19 models passed omr_criteria for train and test data No selected variables. Using the first model in mods_table | | | 0% | |======================================================================| 100% | | | 0% | |======================================================================| 100%No selected variables. Using the first model in mods_table | | | 0% | |=================================== | 50% | |======================================================================| 100% | | | 0% | |=================================== | 50% | |======================================================================| 100%[ FAIL 0 | WARN 1 | SKIP 0 | PASS 37 ] [ FAIL 0 | WARN 1 | SKIP 0 | PASS 37 ] > > proc.time() user system elapsed 50.96 3.09 117.09