betaBasis_k

Construct Bernstein polynomial basis of degree k on omega

internal

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

betaBasis_k function

<dl><dt>omega</dt>
<dd>numeric vector in [0,1] of evaluation points</dd>
<dt>k</dt>
<dd>positive integer for the degree</dd>
<dt>coarsened</dt>
<dd>bool flag indicating whether coarsened or standard Bernstein polynomials are used</dd></dl>

Arguments

Construct Bernstein polynomial basis of degree k on omega — betaBasis_k

<dl>

<dt>omega</dt>
<dd>numeric vector in [0,1] of evaluation points</dd>


<dt>k</dt>
<dd>positive integer for the degree</dd>


<dt>coarsened</dt>
<dd>bool flag indicating whether coarsened or standard Bernstein polynomials are used</dd>

</dl>

betaBasis_k: Construct Bernstein polynomial basis of degree k on omega

Description

Usage

Arguments