Statistical Analysis of Discrete-valued Time Series by Parsimonious High-order Markov Chains
Problems of statistical analysis of discrete-valued time series are considered. Two approaches for construction of parsimonious (small-parametric) models for observed discrete data are proposed based on high-order Markov chains. Consistent statistical estimators for parameters of the developed mode...
Main Author: | Yuriy Kharin |
---|---|
Format: | Article |
Language: | English |
Published: |
Austrian Statistical Society
2020-04-01
|
Series: | Austrian Journal of Statistics |
Online Access: | http://www.ajs.or.at/index.php/ajs/article/view/1132 |
Similar Items
-
Markov Chain of Conditional Order: Properties and Statistical Analysis
by: Yuriy Kharin, et al.
Published: (2014-06-01) -
High-order Vector Markov Chain with Partial Connections in Data Analysis
by: Yuriy Kharin, et al.
Published: (2017-04-01) -
Statistical Analysis of Discrete Time Series Based on the MC(s; r)–Model
by: Yuriy Kharin, et al.
Published: (2016-02-01) -
“Plug-in” Statistical Forecasting of Vector Autoregressive Time Series with Missing Values
by: Yuriy Kharin, et al.
Published: (2016-04-01) -
A New Improved Parsimonious Multivariate Markov Chain Model
by: Chao Wang, et al.
Published: (2013-01-01)