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The linear exponential distribution is a generalization of the exponentialand Rayleigh distributions. This distribution is one of the best models to fitdata with increasing failure rate (IFR). But it does not provide a reasonablefit for modeling data with decreasing failure rate (DFR) and bathtub shapedfailure rate (BTFR). To overcome this drawback, we propose a new record-basedtransmuted generalized linear exponential (RTGLE) distribution by using thetechnique of Balakrishnan and He (2021). The family of RTGLE distributions ismore flexible to fit the data sets with IFR, DFR, and BTFR, and alsogeneralizes several well-known models as well as some new record-basedtransmuted models. This paper aims to study the statistical properties of RTGLEdistribution, like, the shape of the probability density function and hazardfunction, quantile function and its applications, moments and its generatingfunction, order and record statistics, Renyi entropy. The maximum likelihoodestimators, least squares and weighted least squares estimators,Anderson-Darling estimators, Cramer-von Mises estimators of the unknownparameters are constructed and their biases and mean squared errors arereported via Monte Carlo simulation study. Finally, the real data set based onfailure time illustrates the goodness of fit and applicability of the proposeddistribution; hence, suitable recommendations are forwarded.

Record-Based Transmuted Generalized Linear Exponential Distribution with Increasing, Decreasing and Bathtub Shaped Failure Rates