HyperparametersSingleBatch: Create an object of class 'HyperparametersSingleBatch' for...

In scristia/CNPBayes: Bayesian mixture models for copy number polymorphisms

Description

Create an object of class 'HyperparametersSingleBatch' for the single batch mixture model

Usage

HyperparametersSingleBatch(
  k = 0L,
  mu.0 = 0,
  tau2.0 = 0.4,
  eta.0 = 32,
  m2.0 = 0.5,
  alpha,
  beta = 0.1,
  a = 1.8,
  b = 6,
  dfr = 100
)

Arguments

k	length-one integer vector specifying number of components (typically 1 <= k <= 4)
mu.0	length-one numeric vector of the mean for the normal prior of the component means
tau2.0	length-one numeric vector of the variance for the normal prior of the component means
eta.0	length-one numeric vector of the shape parameter for the Inverse Gamma prior of the component variances. The shape parameter is parameterized as 1/2 * eta.0.
m2.0	length-one numeric vector of the rate parameter for the Inverse Gamma prior of the component variances. The rate parameter is parameterized as 1/2 * eta.0 * m2.0.
alpha	length-k numeric vector of the shape parameters for the dirichlet prior on the mixture probabilities
beta	length-one numeric vector for the parameter of the geometric prior for nu.0 (nu.0 is the shape parameter of the Inverse Gamma sampling distribution for the component-specific variances). beta is a probability and must be in the interval [0,1].
a	length-one numeric vector of the shape parameter for the Gamma prior used for sigma2.0 (sigma2.0 is the shape parameter of the Inverse Gamma sampling distribution for the component-specific variances)
b	a length-one numeric vector of the rate parameter for the Gamma prior used for sigma2.0 (sigma2.0 is the rate parameter of the Inverse Gamma sampling distribution for the component-specific variances)
dfr	length-one numeric vector for t-distribution degrees of freedom

Value

An object of class HyperparametersSingleBatch

scristia/CNPBayes documentation built on Aug. 9, 2020, 7:31 p.m.