Function reference • MoMA

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`MoMA`	MoMA: Modern Multivariate Analysis in R
Sparsity Choices
`moma_sparsity_options`	Sparsity-inducing penalty in `MoMA`
`moma_lasso()`	LASSO (least absolute shrinkage and selection operator)
`moma_mcp()`	MCP (minimax concave penalty)
`moma_scad()`	SCAD (smoothly clipped absolute deviation)
`moma_fusedlasso()`	Fused LASSO
`moma_spfusedlasso()`	Sparse fused LASSO
`moma_slope()`	SLOPE (sorted \(\ell\)-one penalized estimation)
`moma_grplasso()`	Group LASSO
`moma_l1tf()`	L1 trend filtering
`moma_cluster()`	Cluster penalty
Smoothness Choices
`moma_smoothness()`	Smoothness-inducing Term
`second_diff_mat()`	Second difference matrix
Selection Scheme of Tuning Parameters
`select_scheme`	Introduction to selection schemes in MoMA
Deflation Schemes
`PCA_deflation`	Deflation Schemes for PCA
`CCA_deflation`	The Deflation Scheme for CCA
`LDA_deflation`	The Deflation Scheme for LDA
Multivariate Models
`moma_R6`	R6 objects for storing and accessing the results of SFPCA / SFLDA / SFCCA
`moma_sfcca()` `moma_scca()` `moma_twscca()` `moma_fcca()` `moma_twfcca()`	Sparse and functional CCA
`moma_sflda()` `moma_slda()` `moma_twslda()` `moma_flda()` `moma_twflda()`	Sparse and functional LDA
`moma_sfpca()` `moma_spca()` `moma_twspca()` `moma_fpca()` `moma_twfpca()`	Sparse and functional PCA
Logging
`moma_logger_level()`	MoMA Package Logging Functionality
`moma_session_info()`	Session Info used for Bug Reporting
Algorithm Settings
`moma_pg_settings()`	Algorithm settings for solving the penalized SVD problem

Reference