Approximate Bayesian estimation for parameters of simple linear bivariate truncated t regression model | Zendy

Elham Abduklreem Hussain | Zendy; Haifa Abduljawaad Saied | Zendy

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Approximate Bayesian estimation for parameters of simple linear bivariate truncated t regression model

Author(s) -

Elham Abduklreem Hussain,

Haifa Abduljawaad Saied

Publication year - 2020

Publication title -

mağallaẗ al-tarbiyaẗ wa-al-ʻilm

Language(s) - English

Resource type - Journals

eISSN - 2664-2530

pISSN - 1812-125X

DOI - 10.33899/edusj.2020.164372

Subject(s) - mathematics , proper linear model , design matrix , statistics , bayesian multivariate linear regression , bayesian linear regression , variance function , polynomial regression , linear regression , bivariate analysis , matrix (chemical analysis) , simple linear regression , regression analysis , regression , bayesian probability , bayesian inference , materials science , composite material

In this paper, it is obtained to approximate estimation for parameters of the two-tailed truncated regression model by Lindely approach. The prior noninformative was used for the regression parameters matrix when the variance matrix is known and the two truncated points are also known. Under the quadratic loss function, the estimates approximations of the regression parameters matrix around zero up to third order moments are obtained.

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