Researches

Research Interests

My research interests include: Time Series Analysis, Forecasting methods, Regression Models, Mathematical Statistics, and Multivariate Statistical Analysis.

We study the efficiency of Artificial Neural Networks (ANNs) for Forecasting in the Presence of Auto-correlated, and consider the robustness of various models, including Autoregressive Integrated Moving Average (ARIMA) and Regression models.

In addition, we study the comparison of estimators in regression models with auto-correlated disturbances: When is Ordinary Least Squares (OLS) efficient? We use computer simulations of time series models to determine those efficiencies of OLS in the presence of auto-correlated disturbances, we consider the robustness of various estimators, including estimated Generalized Least Squares (GLS).

 Publications

(A) Articles in Refereed Journals

  1. Safi, S. K., & White, A. K. (2016). Short and Long-Term Forecasting Using Artificial Neural Networks for Stock Prices in Palestine: A Comparative Study.Electronic Journal of Applied Statistical Analysis. Under Review.
  2. Migdad, M., Safi S., and Nassar, M. (2016). The views of the poor families in the services of the Palestinian national program for social protection In Gaza Strip. IUG Journal of Economics and Business. Under Review.
  3. Safi S. (2016). A Comparison of Artificial Neural Network and Time Series Models for Forecasting GDP in Palestine. American Journal of Theoretical and Applied Statistics, 5(2), pp. 58-63. doi: 10.11648/j.ajtas.20160502.13.

http://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20160502.13.pdf

  1. White, A. K., & Safi, S. K. (2016). The Efficiency of Artificial Neural Networks for Forecasting in the Presence of Autocorrelated Disturbances.International Journal of Statistics and Probability5(2), 51.‏

URL: http://dx.doi.org/10.5539/ijsp.v5n2p51     PDF

  1. Namrouty, K, Safi S., and Enaya, A. (2015). The Effect of Budget Deficit On the Growth of Palestinian Economy. IUG Journal of Economics and Business, 24(1).
  2. Migdad, M., Namrouty, K, Safi S., and Nassar, M. (2015). Attributes and characteristics of poor households in Gaza Strip – measurement indicators. IUG Journal of Economics and Business, 3(1), pp:1-40.

http://www2.iugaza.edu.ps/ar/periodical/articles/1%D8%AF.%20%D9%85%D8%AD%D9%85%D8%AF%20%D9%85%D9%82%D8%AF%D8%A7%D8%AF%20%D9%88%D8%A2%D8%AE%D8%B1%D9%88%D9%86.pdf

  1. Safi, S. K., & Ahmed, R. H. A. S. (2014). Distributions of Generalized Order Statistics and Parameters Estimation of Pareto Distribution in Statistical Explicit Forms.‏ IUG Journal of Natural and Engineering Studies, 22(2), pp: 21-29.

http://www2.iugaza.edu.ps/ar/periodical/articles/Samir%20Print.pdf

  1. Safi, S. K., & Al-Reqep, A. A. (2014). Comparative study of portmanteau tests for the residuals autocorrelation in ARMA models.‏ Science Journal of Applied Mathematics and Statistics, USA, 2(1), pp: 1-13.

http://article.sciencepublishinggroup.com/pdf/10.11648.j.sjams.20140201.11.pdf

  1. Safi, S. K., & Saif, E. A. A. (2014). Using GLS to generate forecasts in regression models with auto-correlated disturbances with simulation and Palestinian market index data. American Journal of Theoretical and Applied Statistics3(1), 6-17.‏

http://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20140301.12.pdf

  1. Safi S., Migdad, M., and Taweel, F. (2014). Building Multiple Regression Model for Electricity Consumption in Gaza Strip. IUG Journal of Natural and Engineering Studies, 22(1), pp:1-24.

http://www2.iugaza.edu.ps/ar/periodical/articles/11د.%20سمير%20صافي%20وآخرون.pdf

  1. Migdad, M., Safi S., and Al-Wawi, A. (2014). ”The Role of Palestinian NGOs in Reducing Poverty in Gaza Strip.” IUG Journal of Economics and Business, 22, No.2, pp: 1-44.

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  1. Safi, S. K. (2013). Artificial Neural Networks Approach to Time Series Forecasting for Electricity Consumption in Gaza Strip.IUG Journal of Natural and Engineering Studies21(2), 1-22.‏

http://resportal.iugaza.edu.ps/articles/s12.pdf

  1. Safi, S. K. (2014). Generalized Heteroskedasticity ACF for Moving Average Models in Explicit Forms.Pakistan Journal of Statistics and Operation Research9(4), 381-393.‏

http://www.pjsor.com/index.php/pjsor/article/view/644/321

  1. Safi, S., & Dawoud, I. (2013). Comparative Study on Forecasting Accuracy among Moving Average Models with Simulation and PALTEL Stock Market Data in Palestine.American Journal of Theoretical and Applied Statistics,2(6), 202-209.‏

http://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20130206.17.pdf

  1. Safi, S. K., & AlSheikh Ahmed, R. H. (2013). Generalized order statistics from generalized exponential distributions in explicit forms.Electronic Journal of Applied Statistical Analysis6(2), 222-237.‏

http://siba-ese.unile.it/index.php/ejasa/article/viewFile/11775/11931#

  1. Safi S. and Al Sheikh Ahmed R. (2013). ”Statistical Estimation Based on Generalized Order Statistics from Kumaraswamy Distribution.” Proceedings, 15th Applied Stochastic Models and Data Analysis (ASMDA2013) International Conference, Mataró (Barcelona), Spain 25 – 28 June 2013, pp:743-750.

http://www.asmda.es/images/1Proceedings_ASMDA_2013_N-S.pdf

  1. Safi, S. K. (2013). Statistics in Noble Qur’an.‏ Proceedings of the First International Conference on Information, Operations Management and Statistics (ICIOMS2013), Kuala Lumpur, Malaysia, September 1-3, 2013.

http://www.ieomrs.com/ioms/2013Proceedings/paper/7.pdf

  1. Safi, S., & Elnamrouty, K. (2013). Building Logistic Regression Model to Identify Key Determinants of Poverty in Palestine.‏ IUG Journal of Natural and Engineering Studies, Vol. 20, No.1, pp: 85-102, ISSN 1726-6807.

http://www.iugaza.edu.ps/ar/periodical/articleد.%20سمير%20صافي%20بعد%20التعديل.pdf

  1. Safi, S. (2011). Explicit Equations for ACF in Autoregressive Processes in the Presence of Heteroscedasticity Disturbances. Journal of Modern Applied Statistical Methods10(2), 625-631.

http://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1337&context=jmasm

  1. Safi, S. (2011). ON SELECTION OF AUTOREGRESSIVE ORDER IN CASE OF INCORRECTLY MODEL SPECIFICATION.Islamic Countries Society of Statistical Sciences, 459.‏ Proceedings of the 11th Islamic Countries Conference on Statistical Sciences (ICCS-11). Lahore, Pakistan. Vol. 21, pp: 459-469.

http://www.isoss.net/downloads/Proc%20ICCS-11.pdf

  1. Safi S. and Al Sheikh Ahmed R. (2011). ”On Distributions of Generalized Order Statistics from Kumaraswamy Distribution in Closed Forms.” The 46th Annual Conference On Statistics, Computer Science, and Operations Research, Institute of Statistical Studies and Research, Cairo University. Conference Proceedings.
  2. Safi, S. (2009). Explicit equations for ACF in the presence of heteroscedasticity disturbances in first-order autoregressive models, AR (1).The Journal of the Islamic University of Gaza17(2), 97-107.‏
  3. Safi, S. (2008). Variance Estimation in Time Series Regression Models. Journal of Modern Applied Statistical Methods,7(2), 506-513.
  4. Safi, S. K. (2008). Explicit Equations to Determine the Variances of Regression Coefficients of OLS and GLS Estimators In An Auto-Correlated Regression Models.The Islamic University Journal (Series of Natural Studies and Engineering) Vol16, 65-74.

https://www.researchgate.net/profile/Samir_Safi2/publication/281975648_Variance_Estimation_in_Time_Series_Regression_Models/links/5600796408aec948c4fa8f34.pdf

  1. Safi S. (2008). “A Statistical Study of the Physicians Self-appraisal and the Identification of Training Needs in the Gaza Strip.” Medical Education & Public Health in Palestine Conference at Islamic University of Gaza.
  2. Safi, S., & White, A. (2006). The Efficiency of OLS In The Presence Of Auto-Correlated Disturbances in Regression Models.Journal of Modern Applied Statistical Methods5(1), 107-117.

http://digitalcommons.wayne.edu/cgi/viewcontent.cgi?article=1264&context=jmasm

  1. Safi, S. K. (2006). Explicit Formulas to Determine the Efficiency of OLS in The Presence of First Order Autoregressive Disturbances in Regression Models. The Journal of the Islamic University of Gaza, Vol. 14, No 1, 147-163.
  2. Safi S. (2005). ”Comparison of Estimators in Regression Models with First and Second Order Autoregressive Disturbances: When is OLS Efficient?” The first Conference of Investment and Finance in Palestine between the Development Potential and Contemporary Challenges Proceedings.

(B) Refereed Books

  1. Safi, S. (2016). Doing Time Series Analysis by E-Views. In process.
  2. Safi, S. & White, A. (2016). Doing Statistical Methods by R. In process.
  3. Safi, S. (2016). Business Mathematics, Al-Umma University, Gaza.
  4. Safi, S. (2014). Introduction to Analysis of Regression Models by EViews, IUG scientific research and graduate studies affairs. Pages 413.
  5. Safi, S. (2014). Introduction to Statistics, Al-Umma University, Gaza. pages 421.
  6. Safi, S. (2009). S-PLUS Programming Language and Applied Statistics, VDM Verlag publisher, http://www.vdm-publishing.com, ISBN: 978-3-639-14790-2, pages 376.
  7. Safi, S. (2008). The Efficiency of OLS in the Presence of Auto- correlated Errors, VDM Verlag publisher, http://www.vdm-publishing.com, ISBN-10: 3639086902, ISBN-13: 978-3639086904, pages 166, 2008.

(C) Studies

  1. Safi S. (2012),”Protection of Livelihoods and Food Assistance in the Occupied Palestinian Territory”, CARE International West Bank and Gaza.

http://www.samirsafi.com/full/care.pdf

  1. Safi S. and Migdad K. (2009),”Comparative Study on the Social, Familial, Marital, Educational and Economic Characteristics of the Households in the Palestinian Territories (1997 – 2007)”, Palestinian Central Bureau of Statistics, December, 2009.

http://82.213.38.42/Portals/_PCBS/Downloads/book1648.pdf

 

Professor of Statistics