LogVeroFuncBUENA: Writting the loglikelihood of the dirichlet

In CoDaLoMic: Compositional Models to Longitudinal Microbiome Data

Writting the loglikelihood of the dirichlet

Description

This function calculates the loglikelihood of the dirichlet for the BPBM model.

Usage

LogVeroFuncBUENA(param, MatrizPBmodelo, E, Tt, especiemodi)

Arguments

param	Vector. Column "mean" of the output of "StudyingParam" function.
MatrizPBmodelo	Matrix with the covariates of the model. In an example with two SPBal and three time points, the covariates are written in the following order: 1 1 1 SPBal_{1,t-1} SPBal_{1,t-2} SPBal_{1,t-3} SPBal_{2,t-1} SPBal_{2,t-2} SPBal_{2,t-3}
E	Number f bacteria in the dataset.
Tt	Number of time points available
especiemodi	Matrix that contains at row i the bacterial taxa of bacteria i at time points t=2,...,Tt.

Value

Returns a number with the value of the dirichlet loglikelihood.

References

Creus-Martí, I., Moya, A., Santonja, F. J. (2022). Bayesian hierarchical compositional models for analysing longitudinal abundance data from microbiome studies. Complexity, 2022.

Examples

set.seed(314)
especie=t(gtools::rdirichlet(n=2, c(1,2,3)))
E=3
Tt=2
MatrizPBmodelo=rbind(c(1,1),c(-0.3,0.4),c(0.3,0.5))
set.seed(314)
est=Estimating_BPBM(especie,
                   Tt,
                   E,
                   MatrizPBmodelo,
                   nn.chain=3,
                   nn.burnin=1000,
                   nn.sample=5000,
                   nn.thin=10)

param=est$SamplesAllChains

especiemodi=especie[,-1]


LogVeroFuncBUENA(param,MatrizPBmodelo,E,Tt,especiemodi)

CoDaLoMic documentation built on April 12, 2025, 2:18 a.m.