Function reference • PPBstats

Design experiment
`design_experiment()`	Provides experimental design for the different situations corresponding to the choosen family of analysis
Format data
`format_data_PPBstats()`	Check and format the data to be used by PPBstats functions
`format_data_PPBstats.data_agro()`	Check and format the data to be used by PPBstats functions for data in agronomic analyses
`format_data_PPBstats.data_agro_HA()`	Check and format the data to be used by PPBstats functions for data agro HA to study local adaptation.
`format_data_PPBstats.data_agro_LF()`	Check and format the data to be used by PPBstats functions for data agro LF to study local adaptation.
`format_data_PPBstats.data_agro_SR()`	Check and format the data to be used by PPBstats functions for data agro SR to study response to selection.
`format_data_PPBstats.data_network()`	Check and format the data to be used by PPBstats functions for network analyses
`format_data_PPBstats.data_organo_hedonic()`	Check and format the data to be used by PPBstats functions for hedonic analyses
`format_data_PPBstats.data_organo_napping()`	Check and format the data to be used by PPBstats functions for napping analyses
`HA_to_LF()`	Transform home away data to local foreign data
`LF_to_HA()`	Transform local foreign data to home away data
Run models
`model_GxE()`	Run AMMI or GGE model
`model_anova()`	Run classic anova model
`model_bh_GxE()`	Run Hierarchical Bayesian GxE model
`model_bh_intra_location()`	Run Hierarchical Bayesian intra-location model
`model_bh_variance_intra()`	Run Hierarchical Bayesian variance-intra model
`model_hedonic()`	Run hedonic analysis
`model_home_away()`	Run Home Away model
`model_local_foreign()`	Run Local Foreign model
`model_napping()`	Run napping analysis
`model_spatial()`	Run spatial row and column model
Check models
`check_model()`	Check if the model went well
`check_model(<fit_model_GxE>)`	Check if the GxE model went well
`check_model(<fit_model_anova>)`	Check if the classic anova model went well
`check_model(<fit_model_bh_GxE>)`	Check if the Hierarchical Bayesian GxE model went well
`check_model(<fit_model_bh_intra_location>)`	Check if the Hierarchical Bayesian intra location model went well
`check_model(<fit_model_bh_variance_intra>)`	Check if the Hierarchical Bayesian variance intra model went well
`check_model(<fit_model_hedonic>)`	Check if the hedonic model went well
`check_model(<fit_model_home_away>)`	Check if the home away model went well
`check_model(<fit_model_local_foreign>)`	Check if the local foreign model went well
`check_model(<fit_model_napping>)`	Check if the napping model went well
`check_model(<fit_model_spatial>)`	Check if the spacial model went well
Mean comparisons
`mean_comparisons()`	Get mean comparisons from `check_model` object
`mean_comparisons(<check_model_GxE>)`	Get mean comparisons from `check_model.fit_model_GxE` object
`mean_comparisons(<check_model_anova>)`	Get mean comparisons from `check_model.fit_model_anova` object
`mean_comparisons(<check_model_bh_GxE>)`	Get mean comparisons from `check_model.fit_model_bh_GxE` object
`mean_comparisons(<check_model_bh_intra_location>)`	Get mean comparisons from `check_model.fit_model_bh_intra_location` object
`mean_comparisons(<check_model_bh_variance_intra>)`	Get mean comparisons from `check_model.fit_model_bh_variance_intra` object
`mean_comparisons(<check_model_hedonic>)`	Get mean comparisons from `check_model.fit_model_hedonic` object
`mean_comparisons(<check_model_home_away>)`	Get mean comparisons from `check_model.fit_model_home_away` object
`mean_comparisons(<check_model_local_foreign>)`	Get mean comparisons from `check_model.fit_model_local_foreign` object
`mean_comparisons(<check_model_spatial>)`	Get mean comparisons from `check_model.fit_model_spatial` object
`mean_comparisons(<predict_the_past_model_bh_GxE>)`	Get mean comparisons from `predict_the_past_model_bh_GxE` object
`mean_comparisons_freq_anova()`	mean comparisons for frequentist analysis
Parameter groups
`parameter_groups()`	Get groups of parameters based on multivariate analysis
`parameter_groups_model_GxE()`	Get matrix with variables in column and effects in row from `check_model.fit_model_GxE`
`parameter_groups_model_anova()`	Get matrix with variables in column and effects in row from `check_model.fit_model_anova`
`parameter_groups_model_bh_GxE()`	Get matrix with variables in column and effect in row from `check_model.fit_model_bh_GxE`
`parameter_groups_model_spatial()`	Get matrix with variables in column and effects in row from `check_model.fit_model_spatial`
Plot
`plot.PPBstats`	Get ggplot to visualize output within the PPBstats package
`plot(<biplot_GxE>)`	Get ggplot to visualize output from `biplot_data.check_model_GxE`
`plot(<biplot_hedonic>)`	Get ggplot to visualize output from `biplot_data.check_model_hedonic`
`plot(<biplot_napping>)`	Get ggplot to visualize output from `biplot_data.check_model_hedonic`
`plot(<check_model_GxE>)`	Get ggplot to visualize output from `check_model.fit_model_GxE`
`plot(<check_model_anova>)`	Get ggplot to visualize output from `check_model.fit_model_anova`
`plot(<check_model_bh_GxE>)`	Get ggplot to visualize output from `check_model.fit_model_bh_GxE`
`plot(<check_model_bh_intra_location>)`	Get ggplot to visualize output from `check_model.fit_model_bh_intra_location`
`plot(<check_model_bh_variance_intra>)`	Get ggplot to visualize output from `check_model.fit_model_bh_variance_intra`
`plot(<check_model_hedonic>)`	Get ggplot to visualize output from `check_model.fit_model_hedonic`
`plot(<check_model_home_away>)`	Get ggplot to visualize output from `check_model.fit_model_home_away`
`plot(<check_model_local_foreign>)`	Get ggplot to visualize output from `check_model.fit_model_local_foreign`
`plot(<check_model_napping>)`	Get ggplot to visualize output from `check_model.fit_model_napping`
`plot(<check_model_spatial>)`	Get ggplot to visualize output from `check_model.fit_model_spatial`
`plot(<cross_validation_model_bh_GxE>)`	Get ggplot to visualize output from `cross_validation_model_bh_GxE`
`plot(<data_agro>)`	Plot agro object from format_data_PPBstats.data_agro()
`plot(<data_agro_HA>)`	Plot agro object from format_data_PPBstats.data_agro_HA()
`plot(<data_agro_LF>)`	Plot agro object from format_data_PPBstats.data_agro_LF()
`plot(<data_agro_SR>)`	Plot agro object from format_data_PPBstats.data_agro_SR()
`plot(<data_network>)`	Plot network object from format_data_PPBstats()
`plot(<data_organo_hedonic>)`	Plot hedonic object from `format_data_PPBstats.data_organo_hedonic`
`plot(<data_organo_napping>)`	Plot napping object from `format_data_PPBstats.data_organo_napping`
`plot(<mean_comparisons_model_GxE>)`	Get ggplot to visualize output from `mean_comparisons.check_model_GxE`
`plot(<mean_comparisons_model_anova>)`	Get ggplot to visualize output from `mean_comparisons.check_model_anova`
`plot(<mean_comparisons_model_bh_GxE>)`	Get ggplot to visualize output from `mean_comparisons.check_model_bh_GxE`
`plot(<mean_comparisons_model_bh_intra_location>)`	Get ggplot to visualize output from `mean_comparisons.check_model_bh_intra_location`
`plot(<mean_comparisons_model_hedonic>)`	Get ggplot to visualize output from `mean_comparisons.check_model_GxE`
`plot(<mean_comparisons_model_home_away>)`	Get ggplot to visualize output from `mean_comparisons.check_model_home_away`
`plot(<mean_comparisons_model_local_foreign>)`	Get ggplot to visualize output from `mean_comparisons.check_model_local_foreign`
`plot(<mean_comparisons_model_spatial>)`	Get ggplot to visualize output from `mean_comparisons.check_model_spatial`
`plot(<mean_comparisons_predict_the_past_model_bh_GxE>)`	Get ggplot to visualize output from `mean_comparisons.predict_the_past_model_bh_GxE`
`plot(<parameter_groups>)`	Get ggplot to visualize output from `parameter_groups`
`plot_check_freq_anova()`	plot check freq anova
`plot_descriptive_data()`	Plot agro object from format_data_PPBstats()
`plot_mean_comparisons_freq_anova()`	plot mean comparisons for frequentist analysis
`ggplot_mean_vs_stability()`	Return a "mean vs stability" ggplot based on PCA object
`ggplot_which_won_where()`	Return a "which won where" ggplot based on PCA object
Biplot
`biplot_data()`	Format data for biplot representation
`biplot_data(<check_model_GxE>)`	Compute ecovalence and format PCA results for biplot
`biplot_data(<check_model_hedonic>)`	Format data for CA biplot
`biplot_data(<check_model_napping>)`	Format data for MFA biplot for napping model
Post hoc variation
`post_hoc_variation()`	Plot a barplot with factors' variation for each variable
`post_hoc_variation_model_GxE()`	Get dataframe for factors' variation for each variable from a list whose elements are output from `check_model.fit_model_GxE`
`post_hoc_variation_model_anova()`	Get dataframe for factors' variation for each variable from a list whose elements are output from `check_model.fit_model_anova`
`post_hoc_variation_model_home_away()`	Get dataframe for factors' variation for each variable from a list whose elements are output from `check_model.fit_model_home_away`
`post_hoc_variation_model_local_foreign()`	Get dataframe for factors' variation for each variable from a list whose elements are output from `check_model.fit_model_local_foreign`
`post_hoc_variation_model_spatial()`	Get dataframe for factors' variation for each variable from a list whose elements are output from `check_model.fit_model_spatial`
Others
`splitter_d()`	Some functions used in one or several functions of PPBstats
`comp.parameters()`	Get parameter comparisons two by two or to a given threshold based on MCMC outputs
`cross_validation_model_bh_GxE()`	Run complete cross validation with Hierarchical Bayesian GxE model
`get.at.least.X.groups()`	Get the value of type one error needed to have X groups.
`get.env.info()`	Get regional farms data and satellite farms data
`GxE_build_interaction_matrix()`	Compute interaction matrix for AMMI or GGE model

Reference

Design experiment

Format data

Run models

Check models

Mean comparisons

Parameter groups

Plot

Biplot

Post hoc variation

Others