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2022 | 23 | 3 | 65-78

Article title

Interval shrinkage estimation of the parameter of exponential distribution in the presence of outliers under loss functions

Authors

Content

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Abstracts

EN
In this paper, we studied estimators based on an interval shrinkage with equal weights point shrinkage estimators for all individual target points θ¯ ∈ (θ0, θ1) for exponentially distributed observations in the presence of outliers drawn from a uniform distribution. Estimators obtained from both shrinkage and interval shrinkage were compared, showing that the estimators obtained via the interval shrinkage method perform better. Symmetric and asymmetric loss functions were also used to calculate the estimators. Finally, a numerical study and illustrative examples were provided to describe the results.

Year

Volume

23

Issue

3

Pages

65-78

Physical description

Dates

published
2022

Contributors

author
  • University of Payam Noor, Department of Statistics

References

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  • Dixit, U. J. & Nasiri, P., (2001). Estimation of parameters of the exponential distribution in the presence of outlier generated from uniform distribution, Metron 49, (3-4), pp. 187-198.
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  • Golosnoy, V., & Liesenfeld, R., (2011). Interval shrinkage estimators. Journal of Applied Statistics, 38(3), pp. 465-477.
  • Hawkins, D. M., (1980). Identification of outliers (Vol. 11). London: Chapman and Hall.
  • Nasiri, P. & Ebrahimi, F., (2019), Interval Shrinkage Estimators of Scale Parameter of Exponential Distribution in the Presence of Outliers, Malaysian Journal of Mathematical Sciences, 13(1), pp. 75-85.
  • Nasiri, P., & Jabbari Nooghabi, M., (2009). Estimation of P[Y < X ] for generalized exponential distribution in presence of outlier. Iranian Journal of Numerical Analysis and Optimization, 2(1), pp. 69-80.
  • Nelson, W. B., (1982). Applied life Data Analysis. Wiley, New York.
  • Pandey, B. N., (1997). Testimator of the scale parameter of the exponential distribution using LINEX loss function. Communications in statistics-theory and methods, 26(9), pp. 2191-2202.
  • Roio, J., (1987). On the admissibility of c[X bar] + d with respect to the LINEX loss function. Communications in Statistics-Theory and Methods, 16(12), pp. 3745-3748.
  • Soliman, A. A., (2000). Comparison of LINEX and quadratic Bayes estimators for the Rayleigh distribution. Communications in Statistics-theory and Methods, 29(1), pp. 95-107.
  • Stein, C., (1956). Inadmissibility of the usual estimator for the mean of a multivariate normal distribution. In Proceedings of the Third Berkeley symposium on mathematical statistics and probability, Vol. 1, No. 1, pp. 197-206.
  • Thompson, J. R., (1968). Accuracy borrowing in the estimation of the mean by shrinkage to an interval. Journal of the American Statistical Association, 63(323), pp. 953-963.
  • Varian, H. R., (1975). A Bayesian approach to real estate assessment. Studies in Bayesian econometric and statistics in Honor of Leonard J. Savage, pp. 195-208.
  • Zellner, A., (1986). Bayesian estimation and prediction using asymmetric loss functions. Journal of the American Statistical Association, 81(394), pp. 446-451.

Document Type

Publication order reference

Identifiers

Biblioteka Nauki
2108120

YADDA identifier

bwmeta1.element.ojs-doi-10_2478_stattrans-2022-0030
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