Work place: Department of Statistics & Operations Research, Aligarh Muslim University, Aligarh, India
E-mail: arifislam2@yahoo.com
Website:
Research Interests: Software Construction, Software Development Process, Software Engineering
Biography
Arif-Ul-Islam is working as professor in department of Statistics & Operations Research in Women’s College at Aligarh Muslim University, Aligarh (U.P.), and India. He has more than thirty years of teaching experience. He received his doctorate degree from A.M.U. in 1978. His area of research is Stochastic Process and Reliability Theory. He received his M.Sc. & B.Sc. degree in 1974 and 1972 respectively from same university. He is Gold Medalist in M.Sc.
He has taught at five different Universities in India and abroad. He initiated his career at AMU Aligarh, as Lecturer in 1978. He has taught at University of Kashmir-India, Basrah University-Iraq, Gharyonus University Banghazi-Libya and Gonder University-Ethopia. He has worked as University Grant Commission research associate. He is member of Indian Science Congress and Indian Statistical Association. He has published more than twenty papers in national and international journals of statistics in the field of reliability and life testing. Along with this he has also developed a reliability model for life testing, widely accepted and cited by many researchers in the field of reliability theory. His reliability model is known as Mukherji-Islam failure model. He has guided many Ph.D. students and M.Phil. students, in upcoming area of Accelerated life testing & Software Reliability. Currently he is supervising five scholars in his department. Besides above, he is a great philosopher and debater.
DOI: https://doi.org/10.5815/ijitcs.2014.12.10, Pub. Date: 8 Nov. 2014
The article provides an approach of getting optimal time through graph for Simple step stress accelerated test of inverse weibull distribution. In this we estimate parameters using log linear relationship by maximum likelihood method. Along with this, asymptotic variance and covariance matrix of the estimators are given. Comparison between expected and observed Fisher Information matrix is also shown. Furthermore, confidence interval coverage of the estimators is also presented for checking the precession of estimator. This approach is illustrated with an example using software.
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