Bayesian Method in Linear Model and Constant Time Series Model Using Non- Informative Prior Under Phenology

Abstract

Climate Change is very recent topic at global level for discussion for all of us. Phenology is one of the main bio- indicators to track climate change effects on ecosystem. The present study is devoted to derive results of coherent interest in the field of phenology from Bayesian point of view. In this paper we have developed the phenological probability models using linear model and constant time series model. The comparison of both the models has also been done using the concept of residual sum of square and Bayes’ factor.