Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this article, inference for the modified ibull (MW) distribution under type-II doubly censored sample is discussed. Maximum likelihood estimator (MLE) and Bayes estimators (BEs) based on conjugate and discrete priors are derived for three unknown parameters. The BEs are studied under squared error loss and LINEX error loss functions. The Bayesian prediction (BP) of the l-th ordered observation xl in a sample of size n from MW distribution is obtained. A real life data set and simulation data are used to illustrate the results derived.
['M. S. Kotb', 'Mohammad Z. Raqab']
I am writing a research paper on a idea Inference and prediction for modified Weibull distribution based on doubly censored samples
[{"from": "human", "value": "I am writing a research paper on a idea Inference and prediction for modified Weibull distribution based on doubly censored samples"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this article, inference for the modified ibull (MW) distribution under type-II doubly censored sample is discussed. Maximum likelihood estimator (MLE) and Bayes estimators (BEs) based on conjugate and discrete priors are derived for three unknown parameters. The BEs are studied under squared error loss and LINEX error loss functions. The Bayesian prediction (BP) of the l-th ordered observation xl in a sample of size n from MW distribution is obtained. A real life data set and simulation data are used to illustrate the results derived."}]