mssq: Fit zero-inflated beta regression with random effects

In chvlyl/MSSQ: Multi-Sample Poisson Model for Species Abundance Quantification

Description

Fit zero-inflated beta regression with random effects

Usage

mssq(X, tc, l, N, S, max.diff = 0.001, max.EM.ita = 2000,
  sum.by.markers = NA, species.ind = NA, species.names = NA,
  estimate.phi = TRUE, filter.empty.marker = FALSE, verbose = FALSE)

Arguments

verbose	print the fitting process
logistic.cov	the covariates in logistic component
beta.cov	the covariates in beta component
Y	the response variable in the regression model
subject.ind	the variable for subjects
time.ind	the variable for time points
quad.n	Gaussian quadrature points

Value

abu,theta,phi,converge

Examples

## Not run: 
mssq(logistic.cov=logistic.cov,beta.cov=beta.cov,Y=Y,subject.ind=subject.ind,time.ind=time.ind)

## End(Not run)

chvlyl/MSSQ documentation built on Dec. 1, 2019, 5:22 p.m.