checkSample

Checks if a sample is a suitable argument for some functions within the package.

Estimates parameters in Mixture Transition Distribution (MTD) models, a class of high-order Markov chains. The set of relevant pasts (lags) is selected using either the Bayesian Information Criterion or the Forward Stepwise and Cut algorithms. Other model parameters (e.g. transition probabilities and oscillations) can be estimated via maximum likelihood estimation or the Expectation-Maximization algorithm. Additionally, 'hdMTD' includes a perfect sampling algorithm that generates samples of an MTD model from its invariant distribution. For theory, see Ost & Takahashi (2023) <http://jmlr.org/papers/v24/22-0266.html>.

Maiara Gripp

hdMTD

Inference for High-Dimensional Mixture Transition Distribution
Models

Guilherme Ost

Giulio Iacobelli

checkSample function

<dl><dt>X</dt>
<dd>A vector, a single-column data frame, a list, or a matrix with a
single row or a single column. Must be composed by nonnegative integers.</dd></dl>

Arguments

Checks a sample — checkSample

<dl>

<dt>X</dt>
<dd>A vector, a single-column data frame, a list, or a matrix with a
single row or a single column. Must be composed by nonnegative integers.</dd>

</dl>

checkSample: Checks a sample

Description

Usage

Value

Arguments