HyperparametersSingleBatch {CNPBayes} | R Documentation |
Create an object of class 'HyperparametersSingleBatch' for the single batch mixture model
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)
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 |
An object of class HyperparametersSingleBatch
HyperparametersSingleBatch(k=3)