BernHierModel: Bernoulli hierarchical Beyesian model

In ccshao/maIHB: Inference the Maternal Allele Inheritance via Bayesian Approach

Bernoulli hierarchical Beyesian model

Description

Specify the parameter for hierarchical Beyesian model

Usage

BernHierModel(dat, betaA = 2, betaB = 2, numSavedSteps = 1e+05,
  burnInSteps = 4000, adaptSteps = 1000, thinSteps = 1, parallel = TRUE,
  nChains = 4, saveName = "HierModel")

Arguments

dat	input for the fucntion, should be two colums, first one is read counts of HapI, second is sum of HapI and HapII
betaA	Shape value A for prior beta distribution
betaB	Shape value B for prior beta distribution
numSavedSteps	total simulation steps
burnInSteps	number of burnin steps in MCMC
adaptSteps	number of adapting steps
thinSteps	thin used in estimating posterior distribution
parallel	should MCMC run in parallel?
nChains	number of chains used. Maximum is 4
saveName	prefix for saved Rdata file

Value

MCMC simulations results as a coda object

Note

Scripts have been modified from "Doing Bayesian Data Analysis (2nd)" by John K. Kruschke.

Examples

byesRes.A <- BernHierModel(F1.TypeA[, -1], saveName = "Family1.TypeA")

ccshao/maIHB documentation built on July 9, 2022, 3:48 p.m.