Saifaldin Hashim Kamar
@aliraqia.edu.iq
Finance and Banking/ College of Administration and Economics
Al-Iraqia university
EDUCATION
• Ph.D in Statistics, Faculty of Economics and Political Sciences, Omdurman Islamic University, Sudan, 2010.
• High Diploma in Computer application (Data Security), Institute of Higher Studies in Computer and Information, National Computer Center, Iraq, 1999.
• M.Sc. in Statistics, College of Administration and Economics, University of Baghdad, Iraq, 1998.
• B.Sc. in Statistics, College of Administration and Economics, University of Baghdad, Iraq, 1993.
RESEARCH INTERESTS
• Bayesian Methods
• Growth Curves.
• Linear and Non-Linear Models.
• Bio-statistics.
• Applied Statistics in psychological and educational sciences.
• Using advanced statistical methods in economic, financial, and administrative.
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Hala Kadhum Obead, Saifaldin Hashim Kamar, and Basim Shlaibah Msallam
University of Baghdad College of Science
The parameters of the weighted exponential regression model for panel data are estimated using the maximum likelihood method which represents the aim of this paper. Weekly infection and recovery ratios of COVID-19 data are predicted, where the model is converted from its nonlinear into a linear state using the Taylor series. The novelty of this paper lies in dealing with nonlinear panel data. Furthermore, the panel data of the model are tested to determine whether the data follows fixed or random effects by the Hausman test, as well as the exclusion of the pooled effects because the model does not include the intercept term. The simulation is depended on the generated data to compare the fixed and random effects models for different sample sizes (5, 10, 20, 30). COVID-19 data is used for three Iraqi governorates to represent the panel data model. Three months ,May, June, and July of 2022 are taken to represent the research sample and then predict the ratios of infection and recovery for the next three months. Depending on the Bayesian Information Criterion (BIC) and Akaike's Information Criterion (AIC), the random effects of the weighted exponential regression give better results than the fixed effects. Depending on this, we predict the weekly infection ratios of COVID-19 in Iraq that will decrease during the next ten weeks.
Saifaldin Hashim Kamar, Basim Shlaibah Msallam, and Hassan S. Uraibi
IOP Publishing
It is well-known that grey system theory was put forward in the statistical literature to overcome the problem of partially unknown parameters, therefore it is given the attention of the researchers in many scientific areas. Therefore, many methods have been presented in which the grey system is combined with the Fourier series and others for more accurate prediction. This paper presents a methodology to modify the method of least squares based on Fourier series residuals that are computed by using grey system theory. The objective of this methodology is to improve the estimates of a modified exponential growth model. The performance of the proposed method by using simulation is compared with two famous methods and the results show our proposed method outperforms more than others and it is highly efficient and reliable. On the practical, the new method was used to predict the price of a barrel of crude oil for the OPEC basket for the period from Jul 2019 to Dec 2019, and It can be seen that OPEC basket prices will decline in the end of 2019.
Saifaldin Hashim Kamar and Basim Shlaibah Msallam
Hindawi Limited
The Weibull growth model is an important model especially for describing the growth instability; therefore, in this paper, three methods, namely, generalized maximum entropy, Bayes, and maximum a posteriori, for estimating the four parameter Weibull growth model have been presented and compared. To achieve this aim, it is necessary to use a simulation technique to generate the samples and perform the required comparisons, using varying sample sizes (10, 12, 15, 20, 25, and 30) and models depending on the standard deviation (0.5). It has been shown from the computational results that the Bayes method gives the best estimates.