Application of Bayesian Inference in Time Series Analysis

DOI: 10.18805/BKAP176    | Article Id: BKAP176 | Page : 225-228
Citation :- Application of Bayesian Inference in Time Series Analysis.Bhartiya Krishi Anusandhan Patrika.2019.(34):225-228
Krishna Pada Sarkar, K. N. Singh, Achal Lama, Murari Kumar, Bishal Gurung, Rajeev Kumar, and Vinaykumar L. N. murari.iasri@gmail.com
Address :
ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi-110 012
Submitted Date : 13-01-2020
Accepted Date : 27-12-2019

Abstract

Nowadays, the availability of huge computing facilities makes it easy to adopt a complex algorithm for various problem-solving. As a result, the Bayesian method of parameter estimation, which is based on Bayes’ theorem given by Thomas Bayes, gains its popularity in recent times. Time series modeling and forecasting is an important aspect of modeling. Model performance and forecasting accuracy can be improved largely using a Bayesian approach. In this article, some basic knowledge about Bayesian inference in time series has been discussed.

Keywords

Bayes theorem Inference MCMC algorithm Statistical Modelling Time series.

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