acf_rs

Calculate regime-switching auto-correlation

Simulating and estimating (regime-switching) Markov chain Gaussian
fields with covariance functions of the Gneiting class (Gneiting 2002)
<doi:10.1198/016214502760047113>. It supports parameter estimation by
weighted least squares and maximum likelihood methods, and produces Kriging
forecasts and intervals for existing and new locations.

Tianxia Jia

mcgf

Markov Chain Gaussian Fields Simulation and Parameter Estimation

acf_rs function

<dl><dt>x</dt>
<dd>A univariate numeric time series.</dd>
<dt>label</dt>
<dd>A factor of regime labels.</dd>
<dt>lag_max</dt>
<dd>Maximum lag at which to calculate the acf.</dd>
<dt>demean</dt>
<dd>Logical. Should the covariances be about the sample means?</dd></dl>

Arguments

Calculate regime-switching auto-correlation — acf_rs

<dl>

<dt>x</dt>
<dd>A univariate numeric time series.</dd>


<dt>label</dt>
<dd>A factor of regime labels.</dd>


<dt>lag_max</dt>
<dd>Maximum lag at which to calculate the acf.</dd>


<dt>demean</dt>
<dd>Logical. Should the covariances be about the sample means?</dd>

</dl>

acf_rs: Calculate regime-switching auto-correlation

Description

Usage

Value

Arguments

Examples