The paper addresses the problem of estimation of the model parameters of the logistic exponential distribution based on progressive type-I hybrid censored sample. The maximum likelihood estimates are obtained and computed numerically using Newton-Raphson method. Further, the Bayes estimates are derived under squared error, LINEX and generalized entropy loss functions. Two types (independent and bivariate) of prior distributions are considered for the purpose of Bayesian estimation. It is seen that the Bayes estimates are not of explicit forms.Thus, Lindley's approximation technique is employed to get approximate Bayes estimates. Interval estimates of the parameters based on normal approximate of the maximum likelihood estimates and normal approximation of the log-transformed maximum likelihood estimates are constructed. The highest posterior density credible intervals are obtained by using the importance sampling method. Furthermore, numerical computations are reported to review some of the results obtained in the paper. A real life dataset is considered for the purpose of illustrations.

翻译：本文探讨了根据累进型I混合审查抽样对后勤指数分布模型参数进行估计的问题。根据牛顿-拉夫森方法得出和计算的最大可能性估计数;此外,根据平方误差、LINEX和通用的对流损函数得出贝雅斯估计数;为贝叶斯估计的目的,考虑先前分布的两种(独立和双轨)类型(独立和双轨),发现贝叶斯估计数不是明确的表单。Thus, Lindley的近似技术用来获得近似Bayes估计数。根据对日志转换最大概率估计数的正常近似值和对日志转换最大概率估计数的正常近似值得出参数的跨年度估计数。通过使用重要性抽样方法获得最高的对流密度的可靠间隔。此外,报告数字计算是为了审查在文件中取得的某些结果。为说明目的,考虑真实的生命数据集。