Dr. AMELALSHARGAWI

Department of Statistics Faculty of Science

Full name

Dr. AMEL SAAD AB ALSHARGAWI

َQualifications

Doctor of Phiosophy

Academic Rank

Lecturer

Biography

• Work in General Authority for information Department of Population Statistics -Department of Statistics and Censuses (2001- 2009), including two years as A head of unit labor demographic indicators. • A statistics lecturer cooperating with Medical Sciences College (2007-2010). • A statistics lecturer cooperating with Engineering College (2007-2009). • Currently a faculty member at (Science College - Tripoli University / Tripoli - Libya). Conferences ,Workshops and Committees • The participation with work paper titled: Census and indicators in the First Statistical Conference of Statistical Theory and Practice, (Science College - Tripoli University / Tripoli - Libya -2005). • The participation with work paper titled: Spectral Analysis for Systolic Blood Pressure Data by Using Some Smoothing Windows in the First Statistical Conference of Statistical Theory and Practice, (Science College - Tripoli University / Tripoli - Libya -2007). • A representative of the General Information Authority to participate in the committee to review and evaluate the national report and the preparation of the compound fifth report on the implementation of the Convention on the Elimination of All Forms of Discrimination against Women follower to the Secretariat of the General People's Congress, (Tripoli – Libya-2008). • The Supervisor of review process data Multiple Indicator Cluster Survey, (Tripoli – Libya-2003). • The Supervisor of review process forms the general census of the population, (Tripoli – Libya-2006). • A Member of the Commission national survey of private health facilities, (Tripoli – Libya-2007/2008). • A Member of the Commission survey Operating / General Information Authority, (Tripoli – Libya-2008).

Contact Information

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الاستشهادات

الكل منذ 2017
الإقتباسات
h-index
i10-index

Publications

Nonparametric Robust Estimator for Slop Parameter in Linear Structural Relationship Model

In this study, the linear structural relationship model’s slope parameter is determined by using the proposed robust nonparametric method based on trimmed mean. This method is an upgrade to the nonparametric method that was put forward by Al-Nasser and Ebrahem (2005) by employing trimmed mean for all likely paired slopes rather than median slopes. Simulation study and real data were used to compare the proposed method’s performance versus the traditional maximum likelihood method. In the simulation study, based on both methods’ mean square error, it was inferred that the MLE method breaks down due to the presence of outliers even though its functioning was not affected when there was no outlier in the data set. Based on the real life example, it can be concluded that the performance of our proposed method was quite well in determining slope parameter
Amel Saad Alshargawi, (1-2022)
Publisher's website


Estimate the Slope Parameter in Replicated Linear Structural Relationship Model

ABSTRACT---- Replication of observation allows consistent estimation of slope parameter of a linear structural model when the ratio of variances is unknown or when some external information about parameters is not available. In this paper, we look at the way a linear structural relationship model work by replicating observations with two different estimation methods of slope parameter and different cases of existence of outliers. The maximum likelihood estimate (MLE) and a new nonparametric robust estimation method are used to estimate the slope parameter in replicated linear structural relationship model (RLSRM). The simulation studies and the application of real data are used to investigate the performance of the estimated parameters. Keywords— Maximum likelihood method, A nonparametric method, Trimmed mean, Outlier, Linear structural relationship model with replicated.
AMEL SAAD AB ALSHARGAWI(1-2022)
Publisher's website