summary.SANvi

Summary method for objects of class <code>SANvi</code>.

An efficient tool for fitting nested mixture models based on a shared set of
atoms via Markov Chain Monte Carlo and variational inference algorithms.
Specifically, the package implements the common atoms model (Denti et al., 2023),
its finite version (similar to D'Angelo et al., 2023), and a hybrid finite-infinite
model (D'Angelo and Denti, 2024). All models implement univariate nested mixtures
with Gaussian kernels equipped with a normal-inverse gamma prior distribution
on the parameters. Additional functions are provided to help analyze the
results of the fitting procedure.
References:
Denti, Camerlenghi, Guindani, Mira (2023) <doi:10.1080/01621459.2021.1933499>,
D’Angelo, Canale, Yu, Guindani (2023) <doi:10.1111/biom.13626>,
D’Angelo, Denti (2024) <doi:10.1214/24-BA1458>.

Francesco Denti

sanba

Fitting Shared Atoms Nested Models via MCMC or Variational Bayes

Laura D'Angelo

summary.SANvi function

<dl><dt>object</dt>
<dd>Object of class <code>SANvi</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Summarize the Variational Inference Output — summary.SANvi

<dl>

<dt>object</dt>
<dd>Object of class <code>SANvi</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

summary.SANvi: Summarize the Variational Inference Output

Description

Usage

Value

Arguments