bdp_dw_est_post_stats

Calculating the estimated posterior mean, median and credible region (tv-PSD)

Implementations of Bayesian parametric, nonparametric and semiparametric procedures for univariate and multivariate time series. The package is based on the methods presented in C. Kirch et al (2018) <doi:10.1214/18-BA1126>, A. Meier (2018) <https://opendata.uni-halle.de//handle/1981185920/13470> and Y. Tang et al (2023) <doi:10.48550/arXiv.2303.11561>. It was supported by DFG grants KI 1443/3-1 and KI 1443/3-2.

Renate Meyer

beyondWhittle

Bayesian Spectral Inference for Time Series

Alexander Meier

Claudia Kirch

Matthew C. Edwards

Yifu Tang

bdp_dw_est_post_stats function

<dl><dt>post_sample</dt>
<dd>the posterior sample generated by bdp_dw_mcmc.</dd>
<dt>rescaled_time, freq</dt>
<dd>numeric vectors forming a rectangular grid on which the estimated tv-PSD is evaluated.</dd>
<dt>unif_CR</dt>
<dd>a Boolean value (default FALSE) indicating whether to calculate the uniform credible region
rescaled_time must be in \([0,1]\) and freq must be in \([0,\pi]\).</dd></dl>

Arguments

Calculating the estimated posterior mean, median and credible region (tv-PSD) — bdp_dw_est_post_stats

<dl>

<dt>post_sample</dt>
<dd>the posterior sample generated by bdp_dw_mcmc.</dd>


<dt>rescaled_time, freq</dt>
<dd>numeric vectors forming a rectangular grid on which the estimated tv-PSD is evaluated.</dd>


<dt>unif_CR</dt>
<dd>a Boolean value (default FALSE) indicating whether to calculate the uniform credible region
rescaled_time must be in \([0,1]\) and freq must be in \([0,\pi]\).</dd>

</dl>

bdp_dw_est_post_stats: Calculating the estimated posterior mean, median and credible region (tv-PSD)

Description

Usage

Value

Arguments