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المؤلفNik, Ali Saadati
المؤلفAsgharzadeh, Akbar
المؤلفBaklizi, Ayman
تاريخ الإتاحة2023-11-06T08:19:07Z
تاريخ النشر2023-01-01
اسم المنشورStatistics, Optimization and Information Computing
المعرّفhttp://dx.doi.org/10.19139/soic-2310-5070-1591
الاقتباسNik, A. S., Asgharzadeh, A., & Baklizi, A. (2023). Inference Based on New Pareto-Type Records With Applications to Precipitation and Covid-19 Data. Statistics, Optimization & Information Computing, 11(2), 243-257.‏
الرقم المعياري الدولي للكتاب2311004X
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85152413713&origin=inward
معرّف المصادر الموحدhttp://hdl.handle.net/10576/49049
الملخصWe consider estimation and prediction of future records based on observed records from the new Pareto type distribution proposed recently by Bourguignon et al. (2016), ¡°M. Bourguignon, H. Saulo, R. N. Fernandez, A new Pareto-type distribution with applications in reliability and income data, Physica A, 457 (2016), 166-175¡±. We first obtain the maximum likelihood and Bayesian estimators of the model parameters. We then derive several point predictors for a future record on the basis of the first n observed records. Two real data sets on precipitation and Covid 19 are analysed and a Monte Carlo simulation study has been performed to evaluate the statistical performance of point predictors presented in this paper
راعي المشروعWe are grateful to the editor and reviewer for their valuable comments and suggestions in revising this paper
اللغةen
الناشرInternational Academic Press
الموضوعEstimation
Pareto distribution
Prediction
Records
Simulation
العنوانInference Based on New Pareto-Type Records With Applications to Precipitation and Covid-19 Data
النوعArticle
الصفحات243-257
رقم العدد2
رقم المجلد11
dc.accessType Open Access


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