simMixTime: A simulation function

In Hlch1992/ARZIMM: Statistical modeling and inference of microbial interaction and stability for microbial dynamical systems

Description

Simulation for the ARZIMM model.

Usage

simMixTime(
  baseFdataN2M,
  conFdataN2L,
  timeN,
  interceptM,
  betaMM,
  gammaLM = NULL,
  sigmaM,
  biN2M = NULL,
  family = "Poisson"
)

Arguments

baseFdataN2M	a matrix of absolute counts at baseline time
conFdataN2L	a matrix of concomitant variables
timeN	a vector of the number of time points for each subjects
interceptM	a vector of the intercepts of the non-zero autoregression model
betaMM	a matrix of network table
gammaLM	a matrix of the zero state logit model
sigmaM	a vector of the measurement error standard deviation for the non-zero autoregression model
biN2M	a vector of the random effects for the non-zero autoregression model
family	a character string indicating the distribtuion. default is Poisson

Value

a list of simulations:

otu.tab	a data frame of OTU table
convar	a data frame of concomitant variables
subjid	a vector of subject-time IDs
df	the number of non-zero parameter estimates
zi	a list of the random effects

Examples

require(ARZIMM)
data(parameters)

set.seed(1234)
sim.otu.tab=simMixTime(baseFdataN2M=parameters$baseFdataN2M,conFdataN2L=parameters$conFdataN2L,
timeN=parameters$timeN,interceptM=parameters$interceptM,betaMM=parameters$betaMM,
gammaLM=parameters$gammaLM,sigmaM=parameters$sigmaM,biN2M=parameters$biN2M)

 fdata=cbind(sim.otu.tab[[1]],sim.otu.tab[[2]],subjid=sim.otu.tab[[3]])
 Varname=colnames(sim.otu.tab[[1]])
 Conname=colnames(sim.otu.tab[[2]])[-ncol(sim.otu.tab[[2]])]
 IDname='subjid'
 Tname='time'

 #### NOT RUN
 # ARZIMMresult=ARZIMM::ARZIMM(phy=NULL,Varname = Varname,Conname = Conname,fdata=fdata,
 # IDname = IDname,Tname = Tname)

Hlch1992/ARZIMM documentation built on Feb. 11, 2020, 2:34 a.m.