Aquil Ahmed

Work place: Department of Statistics, University of Kashmir Srinagar, J&K, 190006 State, India



Research Interests: Program Analysis and Transformation, Comparative Programming Language Analysis, Numerical Analysis, Mathematical Analysis, Analysis of Algorithms, Solid Modeling


Aquil Ahmed is Professor at the department of Statistics and Operations Research, A.M.U., Aligarh. He has served the Department of Statistics, University of Kashmir for more than 26 years and is the Founder Head, Department of Statistics, University of Kashmir, Srinagar and functioned as the Dean, Faculty of Physical & Material Sciences. His research interests are in the areas of Probability distributions, Statistical Modeling, R programming, Regression Analysis, Bayesian Analysis, Operations Research and Nonlinear programming. He has guided eight Ph.D. and fifteen M.Phil scholars and published more than 70 research papers in international and national Journals. He has also worked as a Professor of Statistics at the Qassim University, Saudi Arabia for two and half years (Dec.2008 to June 2011). Prof. Ahmed has organized three international Conferences and delivered extension lectures in Academic Staff Colleges and the Departments of several Universities across the country and has also served as a Visiting Professor at the Asian Institute of Technology, Bangkok during 2016. Professor Ahmed was Vice President of Indian Society for Probability & Statistics during 2015-17.

Author Articles
Bayesian Approach to Generalized Normal Distribution under Non-Informative and Informative Priors

By Saima Naqash S.P Ahmad Aquil Ahmed

DOI:, Pub. Date: 8 Nov. 2018

The generalized Normal distribution is obtained from normal distribution by adding a shape parameter to it. This paper is based on the estimation of the shape and scale parameter of generalized Normal distribution by using the maximum likelihood estimation and Bayesian estimation method via Lindley approximation method under Jeffreys prior and informative priors. The objective of this paper is to see which is the suitable prior for the shape and scale parameter of generalized Normal distribution. Simulation study with varying sample sizes, based on MSE, is conducted in R-software for data analysis.

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