Document Details

Document Type : Thesis 
Document Title :
Adaptive Elastic Net Estimation for Semiparametric Partially Linear Model with Spatio-temporal Data
تقدير الشبكة المرنة التكيفية لنموذج خطي جزئي شبه معلمي باستخدام البيانات المكانية الزمانية
 
Subject : Faculty of Science 
Document Language : Arabic 
Abstract : Modelling spatio-temporal data collected on different sites is a challenge because of the potentially large number of parameters in such data. Accurate statistical methods are needed to model and analyze such data. In this thesis, a semiparametric autoregressive partially linear model is utilized. The main objective is to estimate the parameters using the adaptive elastic net model. The proposed methodology is applied to the daily number of COVID-19 cases in Saudi Arabia by taking into account the potential impact of the daily number of vaccine doses. The results showed the estimation procedures applied in the proposed model are more accurate than other methods of estimation in terms of model fits and prediction. Keywords: Adaptive elastic net, spatio-temporal effect, multivariate adaptive splines regression, semiparametric model, covid-19. 
Supervisor : Dr. Dawlah Alsulami 
Thesis Type : Master Thesis 
Publishing Year : 1444 AH
2023 AD 
Co-Supervisor : Dr. Maha Bakoben 
Added Date : Wednesday, March 15, 2023 

Researchers

Researcher Name (Arabic)Researcher Name (English)Researcher TypeDr GradeEmail
تغريد شموس السلميAlsulami, Taghreed ShumusResearcherMaster 

Files

File NameTypeDescription
 49109.pdf pdf 

Back To Researches Page