HyperparametersMultiBatch: Create an object of class 'HyperparametersMultiBatch' for the...

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

Description

Create an object of class 'HyperparametersMultiBatch' for the batch mixture model

Usage

HyperparametersMultiBatch(
  k = 3L,
  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 of the normal prior for 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, tau2_h. The shape parameter is parameterized as 1/2 * eta.0. In the batch model, tau2_h describes the inter-batch heterogeneity of means for component h.
m2.0	length-one numeric vector of the rate parameter for the Inverse Gamma prior of the component variances, tau2_h. The rate parameter is parameterized as 1/2 * eta.0 * m2.0. In the batch model, tau2_h describes the inter-batch heterogeneity of means for component h.
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. Together, nu.0 and sigma2.0 model inter-component heterogeneity in 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 HyperparametersBatch

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