AM_emp_bayes_uninorm: compute the hyperparameters of an Normal-Inverse-Gamma...

In AntMAN: Anthology of Mixture Analysis Tools

Description

This function computes the hyperparameters of a Normal Inverse-Gamma distribution using an empirical Bayes approach. More information about how these hyperparameters are determined can be found here: Bayes and empirical Bayes: do they merge? \insertCitepetrone2012bayesAntMAN.

Usage

AM_emp_bayes_uninorm(y, scEmu = 1, scEsig2 = 3, CVsig2 = 3)

Arguments

y	The data y. If y is univariate, a vector is expected. Otherwise, y should be a matrix.
scEmu	a positive value (default=1) such that marginally E(μ) = s^2*scEmu, where s^2 is the sample variance.
scEsig2	a positive value (default=3) such that marginally E(σ^2) = s^2*scEsig2, where s^2 is the sample variance.
CVsig2	The coefficient of variation of σ^2 (default=3).

Value

an object of class AM_mix_hyperparams, in which hyperparameters m0, k0, nu0 and sig02 are specified. To understand the usage of these hyperparameters, please refer to AM_mix_hyperparams_uninorm.

AntMAN documentation built on July 23, 2021, 5:08 p.m.