Bayesian semiparametric regression using spline

Joint Authors

Muhaysin, Amirah Jabir
Abd al-Husayn, Ammar Muslim

Source

al-Qadisiyah Journal for Computer Science and Mathematics

Issue

Vol. 5, Issue 2 (31 Dec. 2013), pp.111-122, 12 p.

Publisher

University of al-Qadisiyah College of computer Science and Information Technology

Publication Date

2013-12-31

Country of Publication

Iraq

No. of Pages

12

Main Subjects

Mathematics

Abstract EN

In this paper, we consider semiparametric regression model where the mean function of this model has two part, the parametric ( first part ) is assumed to be linear function of p-dimensional covariates and nonparametric ( second part ) is assumed to be a smooth penalized spline.

By using a convenient connection between penalized splines and mixed models, we can representation semiparametric regression model as mixed model.

Bayesian approach is employed to making inferences on the resulting mixed model coefficients, and we prove some theorems about posterior.

American Psychological Association (APA)

Muhaysin, Amirah Jabir& Abd al-Husayn, Ammar Muslim. 2013. Bayesian semiparametric regression using spline. al-Qadisiyah Journal for Computer Science and Mathematics،Vol. 5, no. 2, pp.111-122.
https://search.emarefa.net/detail/BIM-971619

Modern Language Association (MLA)

Muhaysin, Amirah Jabir& Abd al-Husayn, Ammar Muslim. Bayesian semiparametric regression using spline. al-Qadisiyah Journal for Computer Science and Mathematics Vol. 5, no. 2 (2013), pp.111-122.
https://search.emarefa.net/detail/BIM-971619

American Medical Association (AMA)

Muhaysin, Amirah Jabir& Abd al-Husayn, Ammar Muslim. Bayesian semiparametric regression using spline. al-Qadisiyah Journal for Computer Science and Mathematics. 2013. Vol. 5, no. 2, pp.111-122.
https://search.emarefa.net/detail/BIM-971619

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 122

Record ID

BIM-971619