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About the Project

Selecting a suitable statistical distribution for modelling and analysing data is very important to achieve more accurate decisions. Over the years, many statistical distributions have been proposed to fit different data shapes. Applying classical distributions to fit these data sets may lead to inaccurate results. Hence, the need for modifying the standard distributions is clear. Hence, developing new distributions is of great interest to obtain a more flexible distribution that estimates the data accurately and arrives at valid conclusions. The most popular distributions used for fitting lifetime data are gamma, exponential and Weibull distributions. The exponential distribution is considered the most important statistical model in reliability analysis. The exponential distribution is suitable for modelling lifetimes but only with a constant failure rate. Generalizations are thus introduced in exponential distribution so that it is possible to analyse lifetime data that may have varying failure rates and can be used as an alternative to gamma and Weibull distributions in specific situations. Also, numerous reliable and flexible lifetime distributions have been proposed as an alternative to these distributions. Moreover, their reliable extensions and mixture models have been introduced in the literature for lifetime data analysis. Recently, many methods have been proposed to obtain more flexible distributions that accurately reflect the data behaviour in many situations. I aim to develop more flexible and reliable models for analysing various data with great accuracy.

Department & Campus

Department of Mathematics, Coimbatore Campus

Any Specific Skillsets Required by Applicants

Knowledge in R software or Python.

Faculty Profile

Statistical Inference, Life Time Models and Count Data Models
Dr. Rajitha C. S.

Assistant Professor, Department of Mathematics, School of Engineering, Coimbatore

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