The linear exponential distribution is a generalization of the exponential and Rayleigh distributions. This distribution is one of the best models to fit data with increasing failure rate (IFR). But it does not provide a reasonable fit for modeling data with decreasing failure rate (DFR) and bathtub shaped failure rate (BTFR). To overcome this drawback, we propose a new record-based transmuted generalized linear exponential (RTGLE) distribution by using the technique of Balakrishnan and He (2021). The family of RTGLE distributions is more flexible to fit the data sets with IFR, DFR, and BTFR, and also generalizes several well-known models as well as some new record-based transmuted models. This paper aims to study the statistical properties of RTGLE distribution, like, the shape of the probability density function and hazard function, quantile function and its applications, moments and its generating function, order and record statistics, Renyi entropy. The maximum likelihood estimators, least squares and weighted least squares estimators, Anderson-Darling estimators, Cramer-von Mises estimators of the unknown parameters are constructed and their biases and mean squared errors are reported via Monte Carlo simulation study. Finally, the real data set based on failure time illustrates the goodness of fit and applicability of the proposed distribution; hence, suitable recommendations are forwarded.
翻译:线性指数分布是指数分布和Rayleigh分布的概括性。 此分布是将数据组与不断上升的故障率( IFR) 匹配的最佳模型之一。 但是, 它并不能为以不断下降的故障率( DFR) 和浴缸形状的故障率( BTFR) 进行模型化数据提供合理适合。 为了克服这一退步, 我们建议使用 Balakrishnan 和 He (2021) 的技术, 使用基于记录的新转基因通用线性指数( RTGLE) 分布。 RTGLE 分布组的组合更灵活, 以适应数据组( IFR、 DFR 和 BTFR ) 匹配数据。 但它的分布是一些众所周知的模型, 以及一些基于记录变异模式的新的变异模式。 本文的目的是研究RTGLE的统计属性, 例如, 概率和危险功能的变异功能, 时间和记录统计的生成功能, Reny 。 最大的可能性估测算器, 和最差最小的最小的最小的最小的最小的最小的 和最小的最小的 缩缩缩缩分布 。