Bhartiya Krishi Anusandhan Patrika
  • Year: 2019
  • Volume: 34
  • Issue: 3and4

Application of bayesian inference in time series analysis

  • Author:
  • Krishna Pada Sarkar, K. N. Singh, Achal Lama, Murari Kumar, Bishal Gurung, Rajeev Kumar, L. N. Vinaykumar
  • Total Page Count: 4
  • Page Number: 225 to 228

ICAR-Indian Agricultural Statistics Research Institute, Pusa, New Delhi-110 012

*Corresponding author's email id murari.iasri@gmail.com

Online published on 28 October, 2020.

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