R: C++ implementation of multivariate structured Normal inverse...

mmsNiWpdfC {NPflow} | R Documentation

## C++ implementation of multivariate structured Normal inverse Wishart probability density function for multiple inputs

### Description

C++ implementation of multivariate structured Normal inverse Wishart probability density function for multiple inputs

### Usage

    mmsNiWpdfC(xi, psi, Sigma, U_xi0, U_psi0, U_B0, U_Sigma0, U_df0, Log = TRUE)

### Arguments

`xi` | data matrix of dimensions `p x n` where columns contain the observed mean vectors.
`psi` | data matrix of dimensions `p x n` where columns contain the observed skew parameter vectors.
`Sigma` | list of length `n` of observed variance-covariance matrices, each of dimensions `p x p`.
`U_xi0` | mean vectors matrix of dimension `p x K`, `K` being the number of distributions for which the density probability has to be evaluated.
`U_psi0` | skew parameter vectors matrix of dimension `p x K`.
`U_B0` | list of length `K` of structured scale matrices, each of dimensions `p x p`.
`U_Sigma0` | list of length `K` of variance-covariance matrices, each of dimensions `p x p`.
`U_df0` | vector of length `K` of degree of freedom parameters.
`Log` | logical flag for returning the log of the probability density function. Defaults is `TRUE`.

### Value

matrix of densities of dimension `K x n`

### References

Hejblum BP, Alkhassim C, Gottardo R, Caron F and Thiebaut R (2019) Sequential Dirichlet Process Mixtures of Multivariate Skew t-distributions for Model-based Clustering of Flow Cytometry Data. The Annals of Applied Statistics, 13(1): 638-660. <doi: 10.1214/18-AOAS1209>. <arXiv: 1702.04407>. https://arxiv.org/abs/1702.04407 https://doi.org/10.1214/18-AOAS1209

[Package NPflow version 0.13.3 Index]