Abdullah al JawarnehJerash University · Department of Mathematics
Abdullah al Jawarneh
Doctor of Philosophy
Applied Statistics
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8
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Introduction
Dr-Abdullah S. Al-jawarneh received his Ph.D. and M.Sc. in Statistics from the School of Mathematical Sciences, Universiti Sains Malaysia (USM), Penang, Malaysia. He completed his B.Sc. in Mathematics and minor in Mathematical statistics from Yarmouk University, Irbid, Jordan.
During his career, he taught several mathematics and statistics courses to the undergraduate students at Najran University, Saudi Arabia, from 2012 to 2019. He is now working as an Assistant Professor in the Department of
Additional affiliations
October 2021 - present
Publications
Publications (8)
In quantile regression models, numerous penalization methods have been developed to deal with ordinary least-squares method problems. Such methods are ridge penalized quantile regression, lasso penalized quantile regression, and elastic net penalized quantile regression which are used for variable selection and regularization and deals with the mul...
The first part of the Hilbert–Huang transformation is named the empirical mode decomposition (EMD). Which employed to decompose the non-stationary and non-linear time series dataset into a finite set of orthogonal decomposition components. These components have been used in several studies as the new predictor variables to predict the behavior of t...
The first part of the Hilbert–Huang transformation is named the empirical mode decomposition (EMD). Which employed to decompose the non-stationary and non-linear time series dataset into a finite set of orthogonal decomposition components. These components have been used in several studies as the new predictor variables to predict the behavior of...
Elastic net (ELNET) regression is a hybrid statistical technique used for regularizing and selecting necessary predictor variables that have a strong effect on the response variable and deal with multicollinearity problem when it exists between the predictor variables. The empirical mode decomposition (EMD) algorithm is used to decompose the nonsta...
The empirical mode decomposition (EMD) method is used to decompose the non-stationary and nonlinear signal into a finite set of orthogonal non-overlapping time scale components that include several intrinsic mode function components and one residual component. Elastic net (ELN) regression is a statistical penalized method used to address multicolli...
In this study, an elastic net (EN) regression model based on the empirical mode decomposition (EMD) algorithm is used in two applications, namely, numerical experiment and actual time series data. EMD is used to analyze a nonstationary and nonlinear signal dataset, which includes a set of orthogonal intrinsic mode functions (IMFs) and residual comp...
This paper conducts empirical analysis to investigate the impact of domestic
shocks relative to that of internal shocks on business cycle fluctuation in several
developed Asian economies. The factors that determine the volume and impacts
of these shocks on business cycle fluctuation are also in the scope of analysis. We
apply a structural vector au...
