fit_model_single

Fits one model given its structure and the observed data. This function can be used for any supported family (see vignette).

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

fit_model_single function

<dl><dt>structure</dt>
<dd>dlm_block: The structural blocks of the model. All block must be completely defined.</dd>
<dt>outcomes</dt>
<dd>dlm_distr or list of dlm_distr objects: The model outcomes.</dd>
<dt>smooth</dt>
<dd>boolean: A flag indicating if the smoothed distribution for the latent states should be calculated.</dd>
<dt>p.monit</dt>
<dd>numeric (optional): The prior probability of changes in the latent space variables that are not part of its dynamic.</dd></dl>

Arguments

Fitting one kDGLM models — fit_model_single

<dl>

<dt>structure</dt>
<dd>dlm_block: The structural blocks of the model. All block must be completely defined.</dd>


<dt>outcomes</dt>
<dd>dlm_distr or list of dlm_distr objects: The model outcomes.</dd>


<dt>smooth</dt>
<dd>boolean: A flag indicating if the smoothed distribution for the latent states should be calculated.</dd>


<dt>p.monit</dt>
<dd>numeric (optional): The prior probability of changes in the latent space variables that are not part of its dynamic.</dd>

</dl>

fit_model_single: Fitting one kDGLM models

Description

Usage

Value

Arguments