plspm v0.4.9
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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.
Functions in plspm
| Name | Description | |
| cereals | Cereals datset | |
| check_args | Check arguments for | |
| check_data | Check Data | |
| check_maxiter | Check maximum number of iterations | |
| college | College datasets | |
| dummy.G | Dummy by Giorgio | |
| alpha | Cronbach's alpha | |
| arizona | Arizona vegetation dataset | |
| check_specs | Check specifications of PLS-PM algorithm | |
| check_tol | Check tolerance threshold | |
| get_boots | Performs bootstrap validation in | |
| get_data_scaled | Scaling data outside | |
| get_PLSR | Internal PLS regression (full data) | |
| get_PLSR_NA | Internal PLS regression with missing values | |
| get_locals_test | Local groups comparison test | |
| get_ord_scale | Non-Metric Ordinal Scale | |
| get_path_scheme | Calculate inner weighting path scheme | |
| get_weights_nonmetric | Outer Weights Non-Metric Data | |
| innerplot | Plot inner model | |
| check_blocks | Check well defined blocks | |
| check_boot | Check bootstrap options | |
| futbol | Futbol dataset from Spain-England-Italy | |
| check_model | Check congruence between inner and outer models | |
| check_modes | Check modes | |
| check_scaling | Check types of measurement scales and metric | |
| check_scheme | Check scheme | |
| get_ave | Calculate AVE (Average Variance Extracted) | |
| get_GQI | Group Quality Index | |
| get_effects | Path coefficient effects for | |
| get_generals | Get general parameters | |
| get_rank | Rank of a non-metric variable | |
| plspm.fit | Basic results for Partial Least Squares Path Modeling | |
| plspm.groups | Two Groups Comparison in PLS-PM | |
| russa | Russett A | |
| russb | Russett B | |
| get_PLSRdoubleQ | get_PLSRdoubleQ | |
| get_alpha | Calculate Cronbach's alpha | |
| get_gof | Goodness-of-fit for | |
| get_inner_summary | Inner summary assessment | |
| is_missing | Presence of missing values | |
| it.reb | Iterative steps of Response-Based Unit Segmentation (REBUS) | |
| quantiplot | Quantification Plot | |
| rebus.pls | Response Based Unit Segmentation (REBUS) | |
| get_rho | Calculate Dillon-Goldstein's rho | |
| local.models | PLS-PM for global and local models | |
| mobile | ECSI Mobile Phone Provider dataset | |
| get_boot_stats | Get data frame with bootstrap statistics | |
| get_num_scale | Non-Metric Numerical Scale | |
| get_numerics | Transform factors in MV into numeric | |
| get_paths | Calculate path coefficients for | |
| get_plsr1 | PLS regression for | |
| normalize | Normalize a vector | |
| offense | Offense dataset | |
| russett | Russett dataset | |
| check_path | Check path matrix | |
| check_plscomp | Check vector of PLS components (for non-metric plspm) | |
| get_dummies | Dummy matrices for categorical manifest variables | |
| get_dummy | Non-Metric Dummy | |
| satisfaction | Satisfaction dataset | |
| wines | Wines dataset | |
| rescale | Rescale Latent Variable Scores | |
| rho | Dillon-Goldstein's rho | |
| technology | Technology data set | |
| test_dataset | Test Data Set Availibility | |
| test_null_weights | Test outer weights convergence within specified maxiter | |
| unidim | Unidimensionality of blocks | |
| get_metric | Type of metric based on scaling measurement | |
| get_nom_scale | Non-Metric Nominal Scale | |
| get_scores | Calculate Latent Variable Scores | |
| get_treated_data | Apply corresponding treatment to MV | |
| plot.plspm | Plots for PLS Path Models | |
| plspm | PLS-PM: Partial Least Squares Path Modeling | |
| get_manifests | Building data matrix with manifest variables | |
| get_unidim | Unidimensionality of reflective blocks | |
| get_weights | Outer Weights | |
| orange | Orange Juice dataset | |
| outerplot | Plot outer model | |
| rebus.test | Permutation Test for REBUS Multi-Group Comparison | |
| res.clus | Clustering on communality and structural residuals | |
| test_factors | Test presence of factors | |
| test_manifest_scaling | Test scaling of selected manifest variables | |
| simdata | Simulated data for REBUS with two groups | |
| spainfoot | Spanish football dataset | |
| No Results! | ||
Vignettes of plspm
| Name | ||
| plspm_introduction.Rnw | ||
| No Results! | ||
Last month downloads
Details
| Type | Package |
| Date | 2015-05-22 |
| URL | https://github.com/gastonstat/plspm |
| BugReports | https://github.com/gastonstat/plspm/issues |
| VignetteBuilder | knitr |
| License | GPL-3 |
| LazyLoad | yes |
| Collate | 'plspm.r' 'auxiliar.r' 'check_arguments.r' 'check_specifications.r' 'get_alpha.r' 'get_ave.r' 'get_boots.r' 'get_dummies.r' 'get_effects.r' 'get_generals.r' 'get_gof.r' 'get_inner_summary.r' 'get_manifests.r' 'get_metric.r' 'get_nom_scale.r' 'get_num_scale.r' 'get_ord_scale.r' 'get_path_scheme.r' 'get_paths.r' 'get_plsr1.r' 'get_PLSRdoubleQ.r' 'get_rank.r' 'get_rho.r' 'get_scores.r' 'get_treated_data.r' 'get_unidim.r' 'get_weights.r' 'get_weights_nonmetric.r' 'innerplot.r' 'outerplot.r' 'plot.plspm.r' 'rescale.r' 'summary_plspm.r' 'test_manifest_scaling.r' 'test_null_weights.r' 'unidimensionality.r' 'test_factors.r' 'russett-data.r' 'plspm.fit.r' 'plspm.groups.r' 'test_dataset.r' 'get_GQI.r' 'get_locals_test.r' 'get_scaled_data.r' 'it.reb.r' 'local.models.r' 'print.rebus.r' 'rebus.pls.r' 'rebus.test.r' 'res.clus.r' 'get_PLSR.r' 'get_PLSR_NA.r' 'quantiplot.r' 'plspm-package.r' |
| NeedsCompilation | no |
| Packaged | 2017-04-22 09:27:48 UTC; ripley |
| Repository | CRAN |
| Date/Publication | 2017-04-23 10:07:11 UTC |
| X-CRAN-Original-Maintainer | Gaston Sanchez |
| X-CRAN-Comment | Orphaned and corrected on 2017-04-21 as check errors were not corrected despite reminders. |
| imports | amap , diagram , shape , tester , turner |
| suggests | FactoMineR , ggplot2 , knitr , plsdepot , reshape , testthat |
| depends | R (>= 3.0.1) |
| Contributors | Laura Trinchera, Giorgio Russolillo |
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