Bayesian Modelling by Method of Normal Regression: A Case of Modelling Gluten Content in terms of Protein Content in a Variety of Wheat
Keywords:
Modelling, Bayesian regression, regression parameters, prior specification, MCMCAbstract
This article is about the Bayesian modelling of the parameters of a simple linear regression with normal errors. It studies the use of non-informative normal priors to the regression parameters. It has an application on modelling gluten content in terms of protein content of a variety of wheat. The exact estimations of credible sets of the regression parameters obtained from real and simulated data by using MCMC. The posterior estimates of the gluten content in terms of protein content are better in this regression model with normal non-informative prior.
Journal of Institute of Science and Technology, 2014, 19(1): 121-128
Downloads
Published
How to Cite
Issue
Section
License
The copyright of the articles is held by the Institute of Science and Technology, Tribhuvan University (IoST- TU). The views and interpretations in this journal are those of the author(s). They are not attributable to the IoST-TU and do not imply the expression of any opinion concerning the legal status of any country, territory, city, area of its authorities, or concerning the delimitation of its frontiers or boundaries. The corresponding author is responsible for any conflict of interest between authors and others.
The articles in the Journal of Institute of Science and Technology are licensed under a Creative Commons Attribution- Share Alike 4.0 International License (CC: BY-NC), which permits use, distribution and reproduction in any medium or format, remix, transfer, and build upon the materials for any purpose, even commercially, provided the original work is properly cited.
