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
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