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Some estimation procedures of the PDF and CDF of the generalized inverted Weibull distribution with comparison | ||
| International Journal of Nonlinear Analysis and Applications | ||
| مقاله 82، دوره 12، شماره 1، مرداد 2021، صفحه 1017-1036 اصل مقاله (821.49 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2020.21419.2257 | ||
| نویسندگان | ||
| Mortaza Ghasemi Cherati1؛ Ezzatallah Baloui Jamkhaneh* 2؛ Einolah Deiri1 | ||
| 1Department of Statistics, Qaemshahr Branch, IslamicAzad University, Qaemshahr, Iran | ||
| 2Department of Statistics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran | ||
| تاریخ دریافت: 13 شهریور 1399، تاریخ بازنگری: 25 مهر 1399، تاریخ پذیرش: 07 آبان 1399 | ||
| چکیده | ||
| Different estimation procedures for the probability density and cumulative distribution functions of the generalized inverted Weibull distribution are discussed. For this purpose, the parametric and non-parametric estimation approaches as maximum likelihood, uniformly minimum variance unbiased, percentile, least squares and weighted least squares estimators are considered and compared. The expectations and mean square error of the maximum likelihood and uniformly minimum variance unbiased estimation are provided in the closed-form whereas, for non-parametric estimation methods (percentile, least squares and weighted least squares), the expectations and mean square error are computed via the simulation data. The Monte Carlo simulations are provided to assess the performances of the proposed estimation methods. Finally, the analysis of the real data set has been presented for illustrative purposes. | ||
| کلیدواژهها | ||
| Generalized inverted Weibull distribution؛ Maximum likelihood estimator؛ Uniformly minimum variance unbiased estimator؛ Percentile estimator؛ Least squares estimator؛ Weighted least squares estimator | ||
| مراجع | ||
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[1] A.Z. Afify and O.A. Mohamed, A new three-parameter exponential distribution with variable shapes for the hazard rate: estimation and applications, J. Math. 8(135) (2020) 1–17. [2] M. Alizadeh, S. Razaei, S.F. Bagheri and S. Nadarajah, Efficient estimation for the generalized exponential distribution, Stat. Pap. 56 (2015a) 1015–1031. [3] M. Alizadeh, S. Rezaei, S. Nadarajah and SF. Bagheri, On the estimation of the inverse Weibull distribution, Data Sci. J. 15 (2017) 167–182. [4] M. Alizadeh, S. Rezaei and S.F. Bagheri, On the estimation for the Weibull distribution, Ann. Data Sci. 2 (2015b)373–390. [5] M. Alizadeh, S.F. Bagheri, E. Baloui Jamkhaneh and S. Nadarajah, Estimates of the PDF and the CDF of the exponentiated Weibull distribution, Braz J. Probab. Stat. 29 (2015c) 695–716. [6] S.F. Bagheri, M. Alizadeh and S. Nadarajah, Efficient estimation of the PDF and the CDF of the exponentiated Gumbel distribution, Commun. Stat. - Simul. Comput. 45 (2016a) 339–361. [7] S.F. Bagheri, M. Alizadeh, S. Nadarajah and E. Deiri, Efficient estimation of the PDF and the CDF of the Weibull extension model, Commun. Stat. - Simul. Comput. 45 (2016b) 2191–2207. [8] S.F. Bagheri, M. Alizadeh, E. Baloui Jamkhaneh and S. Nadarajah, Evaluation and comparison of estimations in the generalized exponential-Poisson distribution, J. Stat. Comput. Simul. 84 (2014) 2345–2360. [9] A.M. Basheer, Alpha power inverse Weibull distribution with reliability application, J. Taibah Univ. Sci. 13(1) (2019) 423–432. [10] K.P. Burnham and DR. Anderson, Multimodel inference: Understanding AIC and BIC in model selection, Sociol. Methods Res. 33 (2004) 261–304. [11] U.J. Dixit and M. Jabbari Nooghabi, Efficient estimation in the Pareto distribution, Stat. Methodol. 7 (2010) 687–691. [12] A. Drapella, Complementary Weibull distribution: unknown or just forgotten, Qual. Reliab. Eng. Int. 9 (1993) 383–385. [13] Y. Fang, Asymptotic equivalence between cross-validations and Akaike information criteria in mixed-effects models, Data Sci. J. 9 (2011) 15–21. [14] A. Flaih, H. Elsalloukh, E. Mendi and M. Milanova, The exponentiated inverted Weibull distribution, Appl. Math. Inf. Sci. 6(2) (2012) 167–171. [15] FR. Gusmao, E.M. Ortega and G.M. Cordeiro, The generalized inverse Weibull distribution, Stat. Pap. 52 (2011) 591–619. [16] K. Jain, N. Singla and S.K. Sharma, The generalized inverse generalized Weibull distribution and its properties, J. Probab. 2014, 1–11. [17] X. Jia, S. Nadarajah and B. Guo, Inference on q-Weibull parameters, Stat. Pap. 61 (2020) 575–593. [18] J.H.K. Kao, A graphical estimation of mixed Weibull parameters in life testing electron tubes, Technometrics. 1 (1959) 389–407. [19] J.H.K. Kao, Computer methods for estimating Weibull parameters in reliability studies, Trans. Reliab. Qual. Control. 13 (1958) 15–22. [20] A.Z. Keller, A.R.R. Kamath and UD. Perera, Reliability analysis of CNC machine tools, Reliab. Eng. Syst. Safe. 3(6) (1982) 449–473. [21] M.S. Khan and R. King, A new class of transmuted inverse Weibull distribution for reliability analysis, Am. J. Math. Manag. Sci. 33(4) (2014) 261–286. [22] M.S. Khan and R. King, New generalized inverse Weibull distribution for lifetime modeling, Commun. Stat. Appl. Methods. 23(2) (2016) 147–161. [23] P. Kumaraswamy, A generalized probability density function for double bounded random process, J. Hydrol. 46(1-2) (1980) 79–88. [24] J.F. Lawless, Statistical Models and Methods for Lifetime Data. John Wiley and Sons, Inc., New York, 1982. [25] S.S. Maiti and I. Mukherjee, On estimation of the PDF and CDF of the Lindley distribution, Commun. Stat. - Simul. Comput. 47(5) (2018) 1370–1381. [26] F. Maleki Jebely, K. Zare and E. Deiri, Efficient estimation of the PDF and the CDF of the inverse Rayleigh distribution, J. Stat. Comput. Simul. 88(1) (2018) 75–88. [27] F. Maleki Jebely and E. Deiri, Efficient estimation of the PDF and the CDF of the Frechet distribution, Ann. Data Sci. 4 (2017) 211–225. [28] F. Maleki Jebely and E. Deiri, Estimation methods for the probability density function and the cumulative distribution function of the Pareto-Rayleigh distribution, J. Stat. 54(1) (2020) 135–151. [29] H.M. Okasha, A.H. El-Baz, A.M.K. Tarabia and A.M. Basheer, Extended inverse Weibull distribution with reliability application, J. Egypt. Math. Soc. 25 (2017) 343–349. [30] M.Q. Shahbaz, S. Shahbaz and N.S. Butt, The Kumaraswamy-inverse Weibull distribution, Pakistan J. Stat. Oper. Res. 8 (2012) 479–489. [31] Y.M. Tripathi, A.K. Mahto and S. Dey, Efficient estimation of the PDF and the CDF of a generalized Logistic distribution, Ann. Data Sci. 4 (2017) 63–81. | ||
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