Bayesian Heteroscedastic Linear Model

Bayesian inference is an approach of statistical inference where Bayes' theorem is adopted to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference has found application in a wide range of fields of endeavour such as science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". The author applied Bayesian inference to Econometrics in order to proffer solution to the problem of error structure.[Heteroscedasticity]

Autorentext

Dr. Oloyede Isiaka holds P.hD degree in Statistics in University of Ilorin in the year 2015, he is currently lecturing in the Department of Statistics, University of Ilorin and he is an expert in Statistical computing with vast knowledge in various fields of Statistics. He is happily married and blessed with children.

Klappentext

Bayesian inference is an approach of statistical inference where Bayes' theorem is adopted to update the probability for a hypothesis as more evidence or information becomes available. Bayesian inference has found application in a wide range of fields of endeavour such as science, engineering, philosophy, medicine, sport, and law. In the philosophy of decision theory, Bayesian inference is closely related to subjective probability, often called "Bayesian probability". The author applied Bayesian inference to Econometrics in order to proffer solution to the problem of error structure.[Heteroscedasticity]