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Bayesian Estimation and Prediction for the Maxwell Failure Distribution Based on Type II Censored Data 被引量:1
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作者 Anwar M. Hossain Gabriel Huerta 《Open Journal of Statistics》 2016年第1期49-60,共12页
We present Bayes estimators, highest posterior density (HPD) intervals, and maximum likelihood estimators (MLEs), for the Maxwell failure distribution based on Type II censored data, i.e. using the first r lifetimes f... We present Bayes estimators, highest posterior density (HPD) intervals, and maximum likelihood estimators (MLEs), for the Maxwell failure distribution based on Type II censored data, i.e. using the first r lifetimes from a group of n components under test. Reliability/Hazard function estimates, Bayes predictive distributions and highest posterior density prediction intervals for a future observation are also considered. Two data examples and a Monte Carlo simulation study are used to illustrate the results and to compare the performances of the different methods. 展开更多
关键词 Bayes Estimator hpd interval Maxwell Distribution MLE PREDICTION Reliability Function
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A parsimonious Bayesian predictive model for forecasting new reported cases of West Nile disease
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作者 Saman Hosseini Lee W.Cohnstaedt +1 位作者 John M.Humphreys Caterina Scoglio 《Infectious Disease Modelling》 CSCD 2024年第4期1175-1197,共23页
Upon researching predictive models related toWest Nile virus disease,it is discovered that there are numerous parameters and extensive information in most models,thus contributing to unnecessary complexity.Another cha... Upon researching predictive models related toWest Nile virus disease,it is discovered that there are numerous parameters and extensive information in most models,thus contributing to unnecessary complexity.Another challenge frequently encountered is the lead time,which refers to the period for which predictions are made and often is too short.This paper addresses these issues by introducing a parsimonious method based on ICC curves,offering a logistic distribution model derived from the vector-borne SEIR model.Unlike existing models relying on diverse environmental data,our approach exclusively utilizes historical and present infected human cases(number of new cases).With a yearlong lead time,the predictions extend throughout the 12 months,gaining precision as new data emerge.Theoretical conditions are derived to minimize Bayesian loss,enhancing predictive precision.We construct a Bayesian forecasting probability density function using carefully selected prior distributions.Applying these functions,we predict monthspecific infections nationwide,rigorously evaluating accuracy with probabilistic metrics.Additionally,HPD credible intervals at 90%,95%,and 99%levels is performed.Precision assessment is conducted for HPD intervals,measuring the proportion of intervals that does not include actual reported cases for 2020e2022. 展开更多
关键词 West nile virus ICC curve Bayesian model Logistic distribution hpd credible interval
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