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Bayesian estimation of inverse weibull distribution scale parameter under the different loss functions

Yıl 2024, Cilt: 42 Sayı: 4, 1108 - 1115, 01.08.2024

Öz

In this paper, the Bayesian estimators for the Inverse Weibull Distribution (IWD) scale param-eter are derived when the shape parameter of distribution is known. The Bayesian estimators for the parameter are obtained by using the Gamma prior under the different types of loss functions such as square error loss function (Self), Entropy loss function (Elf), Precautionary loss function (Plf), Linear exponential loss function (Linexlf) and nonlinear exponential loss function (Nlinexlf). A classical maximum likelihood estimator (mle) for the parameter is also derived. To compare the efficiency of the parameter estimation methods, a simulation study is carried out. The comparison is based on mean square error.

Kaynakça

  • REFERENCES
  • [1] Langlands AO, Pocock SJ, Kerr GR, Gore SM. Long-term survival of patients with breast cancer: A study of the curability of the disease. Br Med J 1979;2:1247–1251. [CrossRef]
  • [2] Bennett S. Log-logistic regression models for survival data. J R Stat Soc 1983;32:165–171. [CrossRef]
  • [3] Kumar SS, Umesh S, Kumar D. Bayesian estimation of parameters of inverse Weibull distribution. J Appl Stat 2013;40:1597–1607. [CrossRef]
  • [4] Kundu D, Howlader H. Bayesian ınference and prediction of the ınverse weibull distribution for type-II censored data. Comput Stat Data Anal 2010;54:1547–1558. [CrossRef]
  • [5] Keller AZ, Kamath ARR. Alternative reliability models for mechanical systems. In proceeding of the 3rd International Conference on Reliability and Maintainability; 1982. pp. 411–415.
  • [6] Calabria R, Pulcini G. Bayes 2-sample prediction for the inverse Weibull distribution. Commun Stat Theory Methods 1994;23:1811–1824. [CrossRef]
  • [7] Helu A, Samawi H. The inverse weibull distribution as a failure model under various loss functions and based on progressive first-failure censored data. Quality Technol Quant Manage 2015;12:517–535. [CrossRef]
  • [8] Bi Q, Gui W. Bayesian and classical estimation of stress-strength reliability for inverse weibull lifetime models. Algorithms 2017;10:71. [CrossRef]
  • [9] Nassar M, Abo-Kasem EE. Estimation of the inverse Weibull parameters under adaptive type-II progressive hybrid censoring scheme. J Comput Appl Math 2017;315:228– 239. [CrossRef]
  • [10] Singh S, Tripathi YM. Estimating the parameters of an inverse Weibull distribution under progressive type-I interval censoring. Stat Papers 2018;59:21–56. [CrossRef]
  • [11] Jana N, Bera S. Estimation of parameters of inverse Weibull distribution and application to multi-component stress-strength model. J Appl Stat 2022;49:169–194. [CrossRef]
  • [12] Basu AP, Ebrahimi N. Bayesian approach to life testing and reliability estimation using asymmetric loss function. J Stat Plan Inference 1992;29:21–31. [CrossRef]
  • [13] Berger JO. Statistical decision theory, foundation, concepts and method. New York, NY, USA: Springer; 1985. [CrossRef]
  • [14] Norstrom JG. The use of precautionary loss functions in risk analysis. IEEE Trans Reliab vol. 1996;45:400–403. [CrossRef]
  • [15] Parsian A, Kirmani SNU. Estimation Under LINEX Loss Function. In: Ullah A, Wan ATK, Chaturvedi A, Dekker M, editors. Handbook of applied econometrics and statistical inference. Boca Raton, FL, USA: CRC Press; 2020. pp. 53–76. [CrossRef]
  • [16] Misra N, Meulen EC. On estimating the mean of the selected normal population under the LINEX loss function. Metrika 2003;58:173–183. [CrossRef]
  • [17] Nematollahi N, Motamed-Shariati F. Estimation of the scale parameter of the selected gamma population under the entropy loss function, communications in statistics. Theory Methods 2009;38;208–221. [CrossRef]
  • [18] Azimi R, Yaghmaei F, Azimi D. Comparison of bayesian estimation methods for rayleigh progressive censored data under the different asymmetric loss function. Int J Appl Math Res 2012;1:452–461. [CrossRef]
  • [19] Ahmad K, Ahmad SP, Ahmed A. Classical and bayesian approach in estimation of scale parameter of ınverse weibull distribution. Math Theory Model 2015;5.
  • [20] Calabria R, Pulcini G. Point estimation under asymmetric loss functions for left-truncated exponential samples. Commun Stat Aeory Methods 1996;25:585–600. [CrossRef]
  • [21] Gencer G, Saraçoğlu B. Comparison of approximate Bayes estimators under different loss functions for parameters of odd Weibull distribution. J Selçuk Univ Nat Appl Sci 2016;5:18–32.
  • [22] Khatun N, Matin MA. A study on LINEX loss function with different estimating methods. Open J Stat 2020;10:52–63. [CrossRef]
  • [23] Sultan KS. Bayesian estimates based on record values from the inverse Weibull lifetime model. Qual Technol Quant Manage 2008;5:363–374. [CrossRef]
  • [24] Islam SAFM, Roy MK, Ali MM. A non-linear exponential (NLINEX) loss function in bayesian analysis. J Korean Data Inform Sci Soc 2004;15:899–910.
Yıl 2024, Cilt: 42 Sayı: 4, 1108 - 1115, 01.08.2024

Öz

Kaynakça

  • REFERENCES
  • [1] Langlands AO, Pocock SJ, Kerr GR, Gore SM. Long-term survival of patients with breast cancer: A study of the curability of the disease. Br Med J 1979;2:1247–1251. [CrossRef]
  • [2] Bennett S. Log-logistic regression models for survival data. J R Stat Soc 1983;32:165–171. [CrossRef]
  • [3] Kumar SS, Umesh S, Kumar D. Bayesian estimation of parameters of inverse Weibull distribution. J Appl Stat 2013;40:1597–1607. [CrossRef]
  • [4] Kundu D, Howlader H. Bayesian ınference and prediction of the ınverse weibull distribution for type-II censored data. Comput Stat Data Anal 2010;54:1547–1558. [CrossRef]
  • [5] Keller AZ, Kamath ARR. Alternative reliability models for mechanical systems. In proceeding of the 3rd International Conference on Reliability and Maintainability; 1982. pp. 411–415.
  • [6] Calabria R, Pulcini G. Bayes 2-sample prediction for the inverse Weibull distribution. Commun Stat Theory Methods 1994;23:1811–1824. [CrossRef]
  • [7] Helu A, Samawi H. The inverse weibull distribution as a failure model under various loss functions and based on progressive first-failure censored data. Quality Technol Quant Manage 2015;12:517–535. [CrossRef]
  • [8] Bi Q, Gui W. Bayesian and classical estimation of stress-strength reliability for inverse weibull lifetime models. Algorithms 2017;10:71. [CrossRef]
  • [9] Nassar M, Abo-Kasem EE. Estimation of the inverse Weibull parameters under adaptive type-II progressive hybrid censoring scheme. J Comput Appl Math 2017;315:228– 239. [CrossRef]
  • [10] Singh S, Tripathi YM. Estimating the parameters of an inverse Weibull distribution under progressive type-I interval censoring. Stat Papers 2018;59:21–56. [CrossRef]
  • [11] Jana N, Bera S. Estimation of parameters of inverse Weibull distribution and application to multi-component stress-strength model. J Appl Stat 2022;49:169–194. [CrossRef]
  • [12] Basu AP, Ebrahimi N. Bayesian approach to life testing and reliability estimation using asymmetric loss function. J Stat Plan Inference 1992;29:21–31. [CrossRef]
  • [13] Berger JO. Statistical decision theory, foundation, concepts and method. New York, NY, USA: Springer; 1985. [CrossRef]
  • [14] Norstrom JG. The use of precautionary loss functions in risk analysis. IEEE Trans Reliab vol. 1996;45:400–403. [CrossRef]
  • [15] Parsian A, Kirmani SNU. Estimation Under LINEX Loss Function. In: Ullah A, Wan ATK, Chaturvedi A, Dekker M, editors. Handbook of applied econometrics and statistical inference. Boca Raton, FL, USA: CRC Press; 2020. pp. 53–76. [CrossRef]
  • [16] Misra N, Meulen EC. On estimating the mean of the selected normal population under the LINEX loss function. Metrika 2003;58:173–183. [CrossRef]
  • [17] Nematollahi N, Motamed-Shariati F. Estimation of the scale parameter of the selected gamma population under the entropy loss function, communications in statistics. Theory Methods 2009;38;208–221. [CrossRef]
  • [18] Azimi R, Yaghmaei F, Azimi D. Comparison of bayesian estimation methods for rayleigh progressive censored data under the different asymmetric loss function. Int J Appl Math Res 2012;1:452–461. [CrossRef]
  • [19] Ahmad K, Ahmad SP, Ahmed A. Classical and bayesian approach in estimation of scale parameter of ınverse weibull distribution. Math Theory Model 2015;5.
  • [20] Calabria R, Pulcini G. Point estimation under asymmetric loss functions for left-truncated exponential samples. Commun Stat Aeory Methods 1996;25:585–600. [CrossRef]
  • [21] Gencer G, Saraçoğlu B. Comparison of approximate Bayes estimators under different loss functions for parameters of odd Weibull distribution. J Selçuk Univ Nat Appl Sci 2016;5:18–32.
  • [22] Khatun N, Matin MA. A study on LINEX loss function with different estimating methods. Open J Stat 2020;10:52–63. [CrossRef]
  • [23] Sultan KS. Bayesian estimates based on record values from the inverse Weibull lifetime model. Qual Technol Quant Manage 2008;5:363–374. [CrossRef]
  • [24] Islam SAFM, Roy MK, Ali MM. A non-linear exponential (NLINEX) loss function in bayesian analysis. J Korean Data Inform Sci Soc 2004;15:899–910.
Toplam 25 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Biyokimya ve Hücre Biyolojisi (Diğer)
Bölüm Research Articles
Yazarlar

Esin Köksal Babacan 0000-0002-9649-5276

Yayımlanma Tarihi 1 Ağustos 2024
Gönderilme Tarihi 29 Kasım 2022
Yayımlandığı Sayı Yıl 2024 Cilt: 42 Sayı: 4

Kaynak Göster

Vancouver Köksal Babacan E. Bayesian estimation of inverse weibull distribution scale parameter under the different loss functions. SIGMA. 2024;42(4):1108-15.

IMPORTANT NOTE: JOURNAL SUBMISSION LINK https://eds.yildiz.edu.tr/sigma/