DGCPCA: Perform PCA for discrete dataset using Gaussian copula
In fanne-stat/DGCPCA: Discrete Gaussian Copula PCA

Perform PCA for discrete dataset using Gaussian copula

DGCPCA(x, npc, ...)

## S3 method for class 'DGCFit'
DGCPCA(x, npc = 5, ...)

## Default S3 method:
DGCPCA(x, npc = 5, maps = TRUE, ...)

`x`	A discrete dataset. Assumed to be all numerical-discrete-valued if `maps = FALSE`.
`npc`	Number of first PCs needed.
`...`	Parameters for `DGCFit`.
`maps`	Logical or a list of vectors of length `ncol(x)`. If FALSE, `x` must be a mapped dataset (i.e. all discrete values are numerical). If TRUE, all values will be mapped to discrete values in [0,1] using `sort(unique(x[,j]))`. If a list of vectors of length `ncol(x)`, values will be mapped to discrete values in [0,1] accoording to the provided list. See `discrete_mapping`.

An object of class DGCPCA with components:

fit: An object of DGCFit. See DGCFit.
npc: Number of first PCs needed.
lambdas: Eigenvalues for the first npc PCs.
rotmat: Rotation matrix.
scores: The first npc surrogate PC scores.
latent_norm: The simulated unobserved multivariate normal random vectors used to generate the surrogate PC scores.