update_NG

Calculate posterior parameter for the Normal-Gamma, assuming that the observed values came from a Normal model from which the prior distribution for the mean and the precision have joint distribution Normal-Gamma

internal

Provide routines for filtering and smoothing, forecasting, sampling and Bayesian analysis of Dynamic Generalized Linear Models using the methodology described in Alves et al. (2024)<doi:10.48550/arXiv.2201.05387> and dos Santos Jr. et al. (2024)<doi:10.48550/arXiv.2403.13069>.

Silvaneo Vieira dos Santos Junior

kDGLM

Bayesian Analysis of Dynamic Generalized Linear Models

Mariane Branco Alves

Hélio dos Santos Migon

update_NG function

<dl><dt>conj.param</dt>
<dd>list: A vector containing the parameters of the Normal-Gamma (mu0,c0,alpha,beta).</dd>
<dt>ft</dt>
<dd>numeric: A vector representing the means from the normal distribution. Not used in the default method.</dd>
<dt>Qt</dt>
<dd>matrix: A matrix representing the covariance matrix of the normal distribution. Not used in the default method.</dd>
<dt>y</dt>
<dd>numeric: A vector containing the observations.</dd>
<dt>parms</dt>
<dd>list: A list of extra known parameters of the distribution. Not used in this kernel.</dd></dl>

Arguments

update_NG — update_NG

<dl>

<dt>conj.param</dt>
<dd>list: A vector containing the parameters of the Normal-Gamma (mu0,c0,alpha,beta).</dd>


<dt>ft</dt>
<dd>numeric: A vector representing the means from the normal distribution. Not used in the default method.</dd>


<dt>Qt</dt>
<dd>matrix: A matrix representing the covariance matrix of the normal distribution. Not used in the default method.</dd>


<dt>y</dt>
<dd>numeric: A vector containing the observations.</dd>


<dt>parms</dt>
<dd>list: A list of extra known parameters of the distribution. Not used in this kernel.</dd>

</dl>

update_NG: update_NG

Description

Usage

Value

Arguments