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Inference for the Pareto Type-I distribution using upper record ranked set sampling scheme | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 10، دوره 15، شماره 8، آبان 2024، صفحه 115-123 اصل مقاله (960.73 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2023.29767.4251 | ||
| نویسنده | ||
| Ehsan Golzade Gervi* | ||
| Department of Statistics, Payame Noor University, Tehran, Iran | ||
| تاریخ دریافت: 09 بهمن 1401، تاریخ بازنگری: 01 اردیبهشت 1402، تاریخ پذیرش: 26 خرداد 1402 | ||
| چکیده | ||
| In some real-life situations, we will face restrictions of time and sample size which cause a researcher to not have access to all of the data. Therefore, it is valuable to study the estimation of parameters based on information of available data. In such situations, using appropriate sampling schemes, to more efficient estimators are important. The aim of the present paper is to study the Bayes estimators of parameters of the Pareto type-I model under different loss functions and compare among them as well as with the classical estimator named maximum likelihood estimator based on upper record ranked set sampling scheme. Here the informative Gamma prior is used as the conjugate prior distribution for finding the Bayes estimator. We also used symmetric loss functions such as squared error loss function and asymmetric loss functions such as linear-exponential loss function. We present the analysis of a Monte Carlo simulation to compare the performance of the estimators with respect to their risks (average loss over sample space) based on upper record ranked set sampling. Finally, one real data set is analyzed to illustrate the performance of the proposed estimators. | ||
| کلیدواژهها | ||
| Pareto type-I model؛ Bayesian estimator؛ Upper record ranked set sampling؛ Loss function؛ maximum likelihood estimator | ||
| مراجع | ||
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[1] M. Ahsanullah, Record Statistics, Nova Science Publishers Inc, Commack, New York, 1995. [2] B.C. Arnold, N. Balakrishnan, and H.N. Nagaraja, Records, New York (NY), Wiley, 1998. [3] R.L. Berger and G. Casella, Statistical Inference, 2nd ed. New York, Brooks/Cole Pub Co., 1990. [4] J.M. Bernardo and A.F.M. Smith, Bayesian Theory, Wiley, New York, 1994. [5] M. Eskandarzadeh, S. Tahmasebi, and M. Afshari, Information measures for record ranked set samples, Ciencia Natura 38 (2016), 554–563. [6] E. Golzade Gervi, P. Nasiri, and M. Salehi, An overview of Bayesian prediction of future record statistics using upper record ranked set sampling scheme, Int. J. Nonlinear Anal. Appl. 12 (2021), 493-507. [7] E. Golzade Gervi, P. Nasiri, and M. Salehi, Comparison of empirical Bayesian estimations and predictions Based on record ranked set sampling scheme with inverse sampling scheme, J. Statist. Sci. 15 (2021), 193–218. [8] A.S. Hassan, M. Abd-Allah, and H.F. Nagy, Bayesian analysis of record statistics based on generalized inverted exponential model, Int. J. Adv. Sci. Eng. Inf. Technol. 8 (2018), 323–335. [9] E.L. Lehmann and G. Casella, Theory of Point Estimation, 2nd ed. New York, Springer-Verlag, 1998. [10] J.S. Maritz and T. Lwin, Empirical Bayes Method, second ed., Chapman and Hall, London, 1989. [11] H.A. Muttlak, W.A. Abu-Dayyeh, and M.F. Saleh, Estimating Pr(Y < X) using ranked set sampling in case of the exponential distribution, Commun. Stat. Theory Meth. 39 (2010), 1855–1868. [12] V. Nevzorov, Records, Mathematical Theory, Translation of Mathematical Monographs No. 194, American Mathematical Society, Providence, RI, 2011. [13] J. Paul and PY. Thomas, Concomitant record ranked set sampling, Commun. Statist.-Theory Meth. 46 (2017), 5918–5940. [14] V. Pareto, Cours dEconomie Politique. Paris: Rouge et Cie, 1897. [15] F. Proschan, Theoretical explanation of observed decreasing failure rate, Technometrics 5 (1963), 375–383. [16] M.Z. Raqab, J. Ahmadi, and M. Doostparast, Statistical inference based on record data from Pareto model, Statistics 41 (2007), 105–118. [17] M.Z. Raqab, A. Asgharzadeh, and R. Valiollahi, Prediction for Pareto distribution based on progressively Type-II censored samples, Comput. Statist. Data Anal. 54 (2010), 1732–1743. [18] A. Sadeghpour, M. Salehi, and A. Nezakati, Estimations of the stress-strength reliability using lower record ranked set sampling scheme under the generalized exponential distribution, Statist. Comput. Simul. 90 (2020), 51–74. [19] A. Safaryian, M. Arashi, and R. Arabi, Improved estimators for stress-strength reliability using record ranked set sampling scheme, Commun. Statist. Simul. Comput. 48 (2019), 2708–2726. [20] M. Salehi and J. Ahmadi, Estimation of stress-strength reliability using record ranked set sampling scheme from the exponential distribution, Filomat 29 (2015), 1149–1162. [21] M. Salehi, J. Ahmadi, and S. Dey, Comparison of two sampling schemes for generating record-breaking data from the proportional hazard rate models, Commun. Statist. Theory Meth. 45 (2016), 3721–3733. [22] M. Salehi and J. Ahmadi, Record ranked set sampling scheme, Metron 72 (2014), 351–365. [23] A. Soliman, Estimations for Preto model using general progressive censored data and asymmetric loss, Commun. Statist. Theory Meth. 37 (2008), 1353–1370. [24] H.R. Varian, A Bayesian approach to real estate assessment, Stud. Bayesian Economet. Statist. Honor Leonard J. 13 (1975), 195–208. [25] A. Zellner, Bayesian estimation and prediction using asymmetric loss function, J. Am. Stat. Assoc. 81 (1986), 446–451. | ||
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