Package: plspm 0.4.9
plspm: Tools for Partial Least Squares Path Modeling (PLS-PM)
Partial Least Squares Path Modeling (PLS-PM) analysis for both metric and non-metric data, as well as REBUS analysis for latent class detection.
Authors:
plspm_0.4.9.tar.gz
plspm_0.4.9.zip(r-4.5)plspm_0.4.9.zip(r-4.4)plspm_0.4.9.zip(r-4.3)
plspm_0.4.9.tgz(r-4.5-any)plspm_0.4.9.tgz(r-4.4-any)plspm_0.4.9.tgz(r-4.3-any)
plspm_0.4.9.tar.gz(r-4.5-noble)plspm_0.4.9.tar.gz(r-4.4-noble)
plspm_0.4.9.tgz(r-4.4-emscripten)plspm_0.4.9.tgz(r-4.3-emscripten)
plspm.pdf |plspm.html✨
plspm/json (API)
NEWS
| # Install 'plspm' in R: |
| install.packages('plspm', repos = c('https://gastonstat.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/gastonstat/plspm/issues
- arizona - Arizona vegetation dataset
- cereals - Cereals datset
- college - College datasets
- futbol - Futbol dataset from Spain-England-Italy
- mobile - ECSI Mobile Phone Provider dataset
- offense - Offense dataset
- orange - Orange Juice dataset
- russa - Russett A
- russb - Russett B
- russett - Russett dataset
- satisfaction - Satisfaction dataset
- simdata - Simulated data for REBUS with two groups
- spainfoot - Spanish football dataset
- technology - Technology data set
- wines - Wines dataset
Last updated 3 years agofrom:bd21cb1530. Checks:1 OK, 7 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 03 2025 |
| R-4.5-win | NOTE | Mar 03 2025 |
| R-4.5-mac | NOTE | Mar 03 2025 |
| R-4.5-linux | NOTE | Mar 03 2025 |
| R-4.4-win | NOTE | Mar 05 2025 |
| R-4.4-mac | NOTE | Mar 03 2025 |
| R-4.3-win | NOTE | Mar 03 2025 |
| R-4.3-mac | NOTE | Mar 03 2025 |
Exports:alphacheck_argscheck_blockscheck_bootcheck_datacheck_maxitercheck_modelcheck_modescheck_pathcheck_plscompcheck_scalingcheck_schemecheck_specscheck_toldummy.Gget_alphaget_aveget_boot_statsget_bootsget_data_scaledget_dummiesget_dummyget_effectsget_generalsget_gofget_GQIget_inner_summaryget_locals_testget_manifestsget_metricget_nom_scaleget_num_scaleget_numericsget_ord_scaleget_path_schemeget_pathsget_PLSRget_PLSR_NAget_plsr1get_PLSRdoubleQget_rankget_rhoget_scoresget_treated_dataget_unidimget_weightsget_weights_nonmetricinnerplotis_missingit.reblocal.modelsnormalizeouterplotplspmplspm.fitplspm.groupsquantiplotrebus.plsrebus.testres.clusrescalerhotest_datasettest_factorstest_manifest_scalingtest_null_weightsunidim
