Package: parameters 0.22.1.7
Daniel Lüdecke
parameters: Processing of Model Parameters
Utilities for processing the parameters of various statistical models. Beyond computing p values, CIs, and other indices for a wide variety of models (see list of supported models using the function 'insight::supported_models()'), this package implements features like bootstrapping or simulating of parameters and models, feature reduction (feature extraction and variable selection) as well as functions to describe data and variable characteristics (e.g. skewness, kurtosis, smoothness or distribution).
Authors:
parameters_0.22.1.7.tar.gz
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parameters_0.22.1.7.tgz(r-4.4-any)parameters_0.22.1.7.tgz(r-4.3-any)
parameters_0.22.1.7.tar.gz(r-4.5-noble)parameters_0.22.1.7.tar.gz(r-4.4-noble)
parameters_0.22.1.7.tgz(r-4.4-emscripten)parameters_0.22.1.7.tgz(r-4.3-emscripten)
parameters.pdf |parameters.html✨
parameters/json (API)
NEWS
| # Install 'parameters' in R: |
| install.packages('parameters', repos = c('https://easystats.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/easystats/parameters/issues
- fish - Sample data set
- qol_cancer - Sample data set
betabootstrapciconfidence-intervalsdata-reductioneasystatsfafeature-extractionfeature-reductionhacktoberfestparameterspcapvaluesregression-modelsrobust-statisticsstandardizestandardized-estimatesstatistical-models
Last updated 2 days agofrom:2e2ce8473e
Exports:bootstrap_modelbootstrap_parameterscici_betwithinci_kenwardci_ml1ci_satterthwaiteclosest_componentcluster_analysiscluster_centerscluster_discriminationcluster_metacluster_performancecompare_modelscompare_parametersconfidence_curveconsonance_functionconvert_efa_to_cfadegrees_of_freedomdemeandescribe_distributiondisplaydofdof_betwithindof_kenwarddof_ml1dof_satterthwaitedominance_analysisefa_to_cfaequivalence_testfactor_analysisformat_df_adjustformat_orderformat_p_adjustformat_parametersget_scoreskurtosismodel_parametersn_clustersn_clusters_dbscann_clusters_elbown_clusters_gapn_clusters_hclustn_clusters_silhouetten_componentsn_factorsn_parametersp_calibratep_functionp_valuep_value_betwithinp_value_kenwardp_value_ml1p_value_satterthwaiteparametersparameters_typepool_parametersprincipal_componentsprint_htmlprint_mdprint_tablerandom_parametersreduce_datareduce_parametersrescale_weightsreshape_loadingsrotated_datase_kenwardse_satterthwaiteselect_parameterssimulate_modelsimulate_parametersskewnesssort_parametersstandard_errorstandardise_infostandardise_parametersstandardise_posteriorsstandardize_infostandardize_namesstandardize_parametersstandardize_posteriorssupported_modelsvisualisation_recipe
Dependencies:bayestestRdatawizardinsight
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Model bootstrapping | bootstrap_model bootstrap_model.default bootstrap_model.merMod |
| Parameters bootstrapping | bootstrap_parameters bootstrap_parameters.default |
| Between-within approximation for SEs, CIs and p-values | ci_betwithin dof_betwithin p_value_betwithin |
| Kenward-Roger approximation for SEs, CIs and p-values | ci_kenward dof_kenward p_value_kenward se_kenward |
| "m-l-1" approximation for SEs, CIs and p-values | ci_ml1 dof_ml1 p_value_ml1 |
| Satterthwaite approximation for SEs, CIs and p-values | ci_satterthwaite dof_satterthwaite p_value_satterthwaite se_satterthwaite |
| Confidence Intervals (CI) | ci.default ci.glmmTMB ci.merMod |
| Cluster Analysis | cluster_analysis |
| Find the cluster centers in your data | cluster_centers |
| Compute a linear discriminant analysis on classified cluster groups | cluster_discrimination |
| Metaclustering | cluster_meta |
| Performance of clustering models | cluster_performance cluster_performance.dbscan cluster_performance.hclust cluster_performance.kmeans cluster_performance.parameters_clusters |
| Compare model parameters of multiple models | compare_models compare_parameters |
| Conversion between EFA results and CFA structure | convert_efa_to_cfa convert_efa_to_cfa.fa efa_to_cfa |
| Degrees of Freedom (DoF) | degrees_of_freedom dof |
| Print tables in different output formats | display.equivalence_test_lm display.parameters_efa display.parameters_efa_summary display.parameters_model display.parameters_sem print_table |
| Dominance Analysis | dominance_analysis |
| Equivalence test | equivalence_test.ggeffects equivalence_test.lm equivalence_test.merMod |
| Principal Component Analysis (PCA) and Factor Analysis (FA) | closest_component factor_analysis predict.parameters_efa principal_components print.parameters_efa rotated_data sort.parameters_efa |
| Sample data set | fish |
| Format the name of the degrees-of-freedom adjustment methods | format_df_adjust |
| Order (first, second, ...) formatting | format_order |
| Format the name of the p-value adjustment methods | format_p_adjust |
| Parameter names formatting | format_parameters format_parameters.default |
| Print comparisons of model parameters | format.compare_parameters print.compare_parameters print_html.compare_parameters print_md.compare_parameters |
| Print model parameters | format.parameters_model print.parameters_model print_html.parameters_model print_md.parameters_model summary.parameters_model |
| Get Scores from Principal Component Analysis (PCA) | get_scores |
| Model Parameters | model_parameters parameters |
| Parameters from ANOVAs | model_parameters.afex_aov model_parameters.aov |
| Parameters from Bayesian Exploratory Factor Analysis | model_parameters.befa |
| Parameters from BayesFactor objects | model_parameters.BFBayesFactor |
| Parameters from Generalized Additive (Mixed) Models | model_parameters.cgam model_parameters.Gam model_parameters.gamm model_parameters.scam |
| Parameters from Mixed Models | model_parameters.clmm model_parameters.clmm2 model_parameters.cpglmm model_parameters.glmmTMB model_parameters.lme model_parameters.merMod model_parameters.mixed model_parameters.MixMod |
| Parameters from Cluster Models (k-means, ...) | model_parameters.dbscan model_parameters.hclust model_parameters.hkmeans model_parameters.kmeans model_parameters.Mclust model_parameters.pam model_parameters.pvclust |
| Parameters from (General) Linear Models | model_parameters.censReg model_parameters.default model_parameters.glm model_parameters.ridgelm |
| Parameters from multinomial or cumulative link models | model_parameters.bifeAPEs model_parameters.bracl model_parameters.clm2 model_parameters.DirichletRegModel model_parameters.mlm |
| Parameters from Hypothesis Testing | model_parameters.glht |
| Parameters from special models | model_parameters.averaging model_parameters.betamfx model_parameters.betaor model_parameters.betareg model_parameters.emm_list model_parameters.glimML model_parameters.glmx model_parameters.marginaleffects model_parameters.metaplus model_parameters.meta_bma model_parameters.meta_random model_parameters.mjoint model_parameters.mvord model_parameters.selection |
| Parameters from hypothesis tests | model_parameters.coeftest model_parameters.htest |
| Parameters from Bayesian Models | model_parameters.brmsfit model_parameters.data.frame model_parameters.draws model_parameters.MCMCglmm model_parameters.stanreg |
| Parameters from multiply imputed repeated analyses | model_parameters.mipo model_parameters.mira |
| Parameters from PCA, FA, CFA, SEM | model_parameters.lavaan model_parameters.PCA model_parameters.principal |
| Parameters from Meta-Analysis | model_parameters.rma |
| Parameters from robust statistical objects in 'WRS2' | model_parameters.t1way |
| Parameters from Zero-Inflated Models | model_parameters.mhurdle model_parameters.zcpglm |
| Find number of clusters in your data | n_clusters n_clusters_dbscan n_clusters_elbow n_clusters_gap n_clusters_hclust n_clusters_silhouette |
| Number of components/factors to retain in PCA/FA | n_components n_factors |
| Calculate calibrated p-values. | p_calibrate p_calibrate.default |
| p-value or consonance function | confidence_curve consonance_function p_function |
| p-values | p_value p_value.default p_value.emmGrid |
| p-values for Bayesian Models | p_value.BFBayesFactor |
| p-values for Models with Special Components | p_value.averaging p_value.betareg p_value.cgam p_value.clm2 p_value.DirichletRegModel |
| p-values for Marginal Effects Models | p_value.betamfx p_value.betaor p_value.poissonmfx |
| p-values for Models with Zero-Inflation | p_value.zcpglm p_value.zeroinfl |
| Type of model parameters | parameters_type |
| Pool Model Parameters | pool_parameters |
| Predict method for parameters_clusters objects | predict.parameters_clusters |
| Sample data set | qol_cancer |
| Summary information from random effects | random_parameters |
| Dimensionality reduction (DR) / Features Reduction | reduce_data reduce_parameters |
| Reshape loadings between wide/long formats | reshape_loadings reshape_loadings.data.frame reshape_loadings.parameters_efa |
| Automated selection of model parameters | select_parameters select_parameters.lm select_parameters.merMod |
| Simulated draws from model coefficients | simulate_model simulate_model.glmmTMB |
| Simulate Model Parameters | simulate_parameters simulate_parameters.default simulate_parameters.glmmTMB |
| Sort parameters by coefficient values | sort_parameters sort_parameters.default |
| Standard Errors | standard_error standard_error.default standard_error.factor standard_error.glmmTMB standard_error.merMod |
| Get Standardization Information | standardise_info standardize_info standardize_info.default |
| Parameters standardization | standardise_parameters standardise_posteriors standardize_parameters standardize_posteriors |
