`moma_sfpca`

creates an `SFPCA`

R6 object and returns it.

`moma_spca`

is a function for performing one-way sparse PCA.

`moma_twspca`

is a function for performing two-way sparse PCA.

`moma_fpca`

is a function for performing one-way functional PCA.

`moma_twfpca`

is a function for performing two-way functional PCA.

moma_sfpca(X, ..., center = TRUE, scale = FALSE, u_sparse = moma_empty(), v_sparse = moma_lasso(), u_smooth = moma_smoothness(), v_smooth = moma_smoothness(), pg_settings = moma_pg_settings(), max_bic_iter = 5, rank = 1, deflation_scheme = "PCA_Hotelling") moma_spca(X, ..., center = TRUE, scale = FALSE, u_sparse = moma_empty(), v_sparse = moma_lasso(), pg_settings = moma_pg_settings(), max_bic_iter = 5, rank = 1, deflation_scheme = "PCA_Hotelling") moma_twspca(X, ..., center = TRUE, scale = FALSE, u_sparse = moma_lasso(), v_sparse = moma_lasso(), pg_settings = moma_pg_settings(), max_bic_iter = 5, rank = 1, deflation_scheme = "PCA_Hotelling") moma_fpca(X, ..., center = TRUE, scale = FALSE, u_smooth = moma_smoothness(), v_smooth = moma_smoothness(), pg_settings = moma_pg_settings(), max_bic_iter = 5, rank = 1, deflation_scheme = "PCA_Hotelling") moma_twfpca(X, ..., center = TRUE, scale = FALSE, u_smooth = moma_smoothness(), v_smooth = moma_smoothness(), pg_settings = moma_pg_settings(), max_bic_iter = 5, rank = 1, deflation_scheme = "PCA_Hotelling")

X | A data matrix, each row representing a sample, and each column a feature. |
---|---|

... | Force users to specify arguments by names. |

center | A logical value indicating whether the variables should be shifted to be zero centered.
Defaults to |

scale | A logical value indicating whether the variables should be scaled to have unit variance.
Defaults to |

u_sparse, v_sparse | An object of class inheriting from " |

u_smooth, v_smooth | An object of class inheriting from " |

pg_settings | An object of class inheriting from " |

max_bic_iter | A positive integer. Defaults to 5. The maximum number of iterations allowed in nested greedy BIC selection scheme. |

rank | A positive integer. Defaults to 1. The maximal rank, i.e., maximal number of principal components to be used. |

deflation_scheme | A string specifying the deflation scheme.
It should be one of In the discussion below, let \(u,v\) be the normalized vectors obtained by scaling the penalized singular vectors. When When When |

An R6 object which provides helper functions to access the results. See `moma_R6`

.

`moma_spca`

: a function for performing one-way sparse PCA`moma_twspca`

: a function for performing two-way sparse PCA`moma_fpca`

: a function for performing one-way functional PCA`moma_twfpca`

: a function for performing two-way functional PCA