Bayesian Estimation of Multiple Covariate of Autoregressive (MC-AR) Model

被引：0
|
作者：
Kumar J. [1 ]
Kumar A. [2 ]
Agiwal V. [3 ]
机构：
[1] Department of Statistics, Central University of Rajasthan, NH-8, Bandersindri, Rajasthan, Ajmer
[2] Department of Applied Science and Humanities, School of Engineering & Science, MIT Art, Design & Technology University, Loni-Kalbhor, Pune
[3] Indian Institute of Public Health, Telangana, Hyderabad
来源：
Annals of Data Science | 2024年 / 11卷 / 04期
关键词：
Autoregressive model; Bayesian inference; Covariate;
D O I：
10.1007/s40745-023-00468-2
中图分类号：
学科分类号：
摘要：
In present scenario, handling covariate/explanatory variable with the model is one of most important factor to study with the models. The main advantages of covariate are it’s dependency on past observations. So, study variable is modelled after explaining both on own past and past and future observation of covariates. Present paper deals estimation of parameters of autoregressive model with multiple covariates under Bayesian approach. A simulation and empirical study is performed to check the applicability of the model and recorded the better results. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
引用
收藏
页码：1291 / 1301
页数：10
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