S.P Ahmad

Work place: Department of Statistics, University of Kashmir, Srinagar, India



Research Interests: Mathematics, Mathematical Analysis, Mathematics of Computing, Computational Mathematics


Sheikh Parvaiz Ahmad is Sr. Assistant Professor at the department of Statistics, University of Kashmir, Jammu and Kashmir, India. His research interests are in the areas of Probability distributions, Bayesian Statistics and including the classical and generalized probability distributions and Bio-statistics. He has published different research articles in different international and national reputed, indexed journals in the field of Mathematical Sciences. He is also refereeing of various mathematical and statistical journals especially Applied Mathematics and information Sciences, Journal of Applied Statistics and Probability, Journal of Applied Statistics and Probability Letters, International Journal of Modern Mathematical Sciences, Journal of Modern and Applied Statistical Methods and Pakistan Journal of Statistics and so on. He has presented several research articles at different international and national conferences and also attended several international and national workshops.

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

By Saima Naqash S.P Ahmad Aquil Ahmed

DOI: https://doi.org/10.5815/ijmsc.2018.04.02, 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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Bayesian Normal and T-K Approximations for Shape Parameter of Type-I Dagum Distribution

By Hummara Sultan Uzma Jan S.P Ahmad

DOI: https://doi.org/10.5815/ijmsc.2018.03.02, Pub. Date: 8 Jul. 2018

Dagum distribution is a statistical distribution used closely for fitting income and wealth distributions. This distribution has wide application in fields like reliability theory survival analysis, actuarial sciences, and meteorological data. In this article, we obtained Bayes estimators for the shape parameter of Dagum distribution using approximation techniques like normal and T-K approximations. Moreover different informative priors have been considered and a simulation study and three real data sets have been considered to study the efficiency of obtained results.

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Bayesian Approximation Techniques of Inverse Exponential Distribution with Applications in Engineering

By Kawsar Fatima S.P Ahmad

DOI: https://doi.org/10.5815/ijmsc.2018.02.05, Pub. Date: 8 Apr. 2018

The present study is concerned with the estimation of Inverse Exponential distribution using various Bayesian approximation techniques like normal approximation, Tierney and Kadane (T-K) Approximation. Different informative and non-informative priors are used to obtain the Baye’s estimate of Inverse Exponential distribution under different approximation techniques. A simulation study has also been conducted for comparison of Baye’s estimates obtained under different approximation using different priors. 

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