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