Special Issue: “The Mixture Transition Distribution Model and Other Models for High-Order Dependencies”
Open Access
- 21 January 2022
- Vol. 14 (2), 206
- https://doi.org/10.3390/sym14020206
Abstract
High-order Markov chains are very useful for the analysis of complex temporal relationships, but they generally require a very high number of parametersKeywords
This publication has 7 references indexed in Scilit:
- The Predictive Power of Transition MatricesSymmetry, 2021
- The Deep Learning LSTM and MTD Models Best Predict Acute Respiratory Infection among Under-Five-Year Old Children in SomalilandSymmetry, 2021
- Optimization of the Mixture Transition Distribution Model Using the March Package for RSymmetry, 2020
- The Use of a Hidden Mixture Transition Distribution Model in Clustering Few but Long Continuous Sequences: An Illustration with Cognitive Skills DataSymmetry, 2020
- Handling Covariates in Markovian Models with a Mixture Transition Distribution Based ApproachSymmetry, 2020
- Confidence Intervals for the Mixture Transition Distribution (MTD) Model and Other Markovian ModelsSymmetry, 2020
- A Model for High‐Order Markov ChainsJournal of the Royal Statistical Society: Series B (Methodological), 1985