Package index • ALASCA

All functions
`ALASCA()`	Create an ALASCA model
`AlascaModel`	R6 Class Representing an ALASCA model
`AlascaPlot`	R6 Class that helps visualizing an ALASCA model
`build_model()`	Organize the ALASCA model construction
`clean_alasca()`	Clean the ALASCA data
`clean_pca()`	Clean the PCA data
`do_pca()`	Perform PCA
`do_reduce_dimensions()`	Perform PCA for Limm-PCA
`do_validate()`	Validate the ALASCA model LMM
`find_missing_predictor_variables()`	Check if predictor variables are missing
`find_missing_response_variables()`	Check if response variables are missing
`flip(<AlascaModel>)`	Flip an ALASCA object
`flip()`	Flip an ALASCA object
`get_bootstrap_data()`	Make bootstrap data set
`get_covars(<AlascaModel>)`	Get coefficients for covariates
`get_covars()`	Get coefficients for covariates
`get_default_scaling_function()`	Get a scaling function
`get_effect_matrix()`	Get effect matrix
`get_loadings(<AlascaModel>)`	Returns model loadings
`get_loadings()`	Returns model scores
`get_pca_function()`	Summary
`get_predictions(<AlascaModel>)`	Returns model predictions
`get_predictions()`	Get coefficients for covariates
`get_regression_coefficients()`	Get regression coefficients
`get_regression_formula()`	Modify formula
`get_regression_predictions()`	Validate underlying regression models
`get_scaling_function()`	Get a scaling function
`get_scores(<AlascaModel>)`	Returns model scores
`get_scores()`	Returns model scores
`get_validation_percentiles()`	Extract percentiles
`get_validation_percentiles_covars()`	Extract percentiles for covariates
`get_validation_percentiles_loading()`	Extract percentiles for loading
`get_validation_percentiles_regression()`	Extract percentiles for regressions
`get_validation_percentiles_score()`	Extract percentiles for scores
`plot_covar()`	Plot covariate coefficients
`plot_covariate()`	Plot covariate coefficients
`plot_covariates()`	Plot covariate coefficients
`plot_mm()`	Plot marginal means
`plot_val()`	Plot covariate coefficients
`prepare_validation_run()`	Make a single validation run
`remove_covars()`	Remove unwanted covariables
`remove_embedded_data()`	Remove df from object
`residuals(<AlascaModel>)`	Prints a marco object
`run_regression()`	Run regressions
`save.AlascaModel()`	Save ALASCA model
`screeplot(<AlascaModel>)`	Get screeplot
`screeplot()`	Get screeplot
`set_method()`	Determine whether to use LM or LMM
`summary(<AlascaModel>)`	Summary

Reference

All functions