plot.bsamdpm

Plots the posterior samples for Bayesian spectral analysis models with Dirichlet process mixture error.

Contains functions to perform Bayesian inference
using a spectral analysis of Gaussian process priors.
Gaussian processes are represented with a Fourier series
based on cosine basis functions. Currently the package
includes parametric linear models, partial linear additive
models with/without shape restrictions, generalized linear
additive models with/without shape restrictions, and
density estimation model. To maximize computational
efficiency, the actual Markov chain Monte Carlo sampling
for each model is done using codes written in FORTRAN 90.
This software has been developed using funding supported by
Basic Science Research Program through the National Research
Foundation of Korea (NRF) funded by the Ministry of Education
(no. NRF-2016R1D1A1B03932178 and no. NRF-2017R1D1A3B03035235).

Beomjo Park

bsamGP

Bayesian Spectral Analysis Models using Gaussian Process Priors

Seongil Jo

Taeryon Choi

plot.bsamdpm function

<dl> <dt>x</dt>
<dd>a <code>bsamdpm</code> object</dd> <dt>...</dt>
<dd>other options to pass to the plotting functions</dd></dl>

Arguments

Plot a bsamdpm object — plot.bsamdpm

<dl>

 <dt>x</dt>
<dd>a <code>bsamdpm</code> object</dd>

 <dt>...</dt>
<dd>other options to pass to the plotting functions</dd>

</dl>

plot.bsamdpm: Plot a bsamdpm object

Description

Usage

Value

Arguments

See Also

Examples