Research Article
BibTex RIS Cite

Year 2020, , 944 - 950, 29.12.2020

Kadir Karakaya , Caner Tanış

https://doi.org/10.17776/csj.766011
Cited By: 5

Abstract

References

  • [1] Amin K. Shanker R. Akash distribution and Its Applications, International Journal of Probability and Statistics, 4 (3) (2015) 65–75.
  • [2] Shanker R., Hagos, F. On modeling of lifetime data using Akash, Shanker, Lindley and exponential distributions, Biometrics & Biostatistics International Journal, 3(6) (2016) 214-224.
  • [3] Shanker R. Shanker distribution and its applications, International journal of statistics and Applications, 5(6) (2015) 338-348.
  • [4] Lindley D.V. Fiducial distributions and Bayes’ Theorem, Journal of the Royal Statistical Society, 20(1) (1958) 102-107.
  • [5] Shanker R., Shukla K. K. On two-parameter Akash distribution, Biom. Biostat. Int. J, 6(5) (2017) 416-425.
  • [6] Shanker R., Shukla K. K., Shanker R., Pratap, A. A generalized akash distribution, Biometric & Biostatistics International Journal, 7(1) (2018) 18-26.
  • [7] Shanker R., Shukla K. K., Leonida T. A. A Two-Parameter Poisson-Akash Distribution with Properties and Applications, International Journal of Probability and Statistics, 7(4) (2018) 114-123.
  • [8] Ganaie R. A., Rajagopalan, V. On Weighted Three Parameters Akash Distribution with Application of Lifetime data, Journal of Xidian University, 14 (4) (2020) 877-893.
  • [9] Gupta R. D., Kundu D. Generalized exponential distribution: different method of estimations, Journal of Statistical Computation and Simulation, 69(4) (2001) 315-337.
  • [10] Kundu D., Raqab M. Z. Generalized Rayleigh distribution: different methods of estimations, Computational statistics & data analysis, 49(1) (2005) 187-200.
  • [11] Mazucheli J., Louzada F., Ghitany M. E. Comparison of estimation methods for the parameters of the weighted Lindley distribution, Applied Mathematics and Computation, 220 (2013) 463-471.
  • [12] Dey S., Dey T., Kundu D. Two-parameter Rayleigh distribution: different methods of estimation, American Journal of Mathematical and Management Sciences, 33(1) (2014) 55-74.
  • [13] Mohammadi K., Alavi O., Mostafaeipour A., Goudarzi N., Jalilvand M. Assessing different parameters estimation methods of Weibull distribution to compute wind power density, Energy Conversion and Management, 108 (2016) 322-335.
  • [14] Dey S., Zhang C., Asgharzadeh A., Ghorbannezhad M. Comparisons of methods of estimation for the NH distribution, Annals of Data Science, 4(4) (2017) 441-455.
  • [15] Shanker R. Sujatha distribution and its applications, Statistics in Transition-New series, 17(3) (2016) 391-410.
  • [16] Murthy D. N. P., Xie M., Jiang R. Weibull Models, New York: Wiley, (2004).

Different methods of estimation for the one parameter Akash distribution

Year 2020, , 944 - 950, 29.12.2020

Kadir Karakaya , Caner Tanış

https://doi.org/10.17776/csj.766011
Cited By: 5

Abstract

Akash distribution is a mixture of an exponential distribution and a gamma distribution with certain mixing proportions. Although the maximum likelihood estimation method has been proposed for the Akash distribution, there is no comprehensive comparison of different methods of estimation in the literature. This study provides five different methods of estimation, such as maximum likelihood, least-squares, weighted least-squares, Anderson-Darling, and Crámer–von-Mises for Akash distribution. We consider a comprehensive Monte Carlo simulation study to compare the performances of these methods via the biases and mean-squared errors of these estimators. Also, a real data application is performed. 

Keywords

Akash distribution Maximum likelihood method Least-squares method weighted Least-squares method Crámer–von-Mises estimation method

References

  • [1] Amin K. Shanker R. Akash distribution and Its Applications, International Journal of Probability and Statistics, 4 (3) (2015) 65–75.
  • [2] Shanker R., Hagos, F. On modeling of lifetime data using Akash, Shanker, Lindley and exponential distributions, Biometrics & Biostatistics International Journal, 3(6) (2016) 214-224.
  • [3] Shanker R. Shanker distribution and its applications, International journal of statistics and Applications, 5(6) (2015) 338-348.
  • [4] Lindley D.V. Fiducial distributions and Bayes’ Theorem, Journal of the Royal Statistical Society, 20(1) (1958) 102-107.
  • [5] Shanker R., Shukla K. K. On two-parameter Akash distribution, Biom. Biostat. Int. J, 6(5) (2017) 416-425.
  • [6] Shanker R., Shukla K. K., Shanker R., Pratap, A. A generalized akash distribution, Biometric & Biostatistics International Journal, 7(1) (2018) 18-26.
  • [7] Shanker R., Shukla K. K., Leonida T. A. A Two-Parameter Poisson-Akash Distribution with Properties and Applications, International Journal of Probability and Statistics, 7(4) (2018) 114-123.
  • [8] Ganaie R. A., Rajagopalan, V. On Weighted Three Parameters Akash Distribution with Application of Lifetime data, Journal of Xidian University, 14 (4) (2020) 877-893.
  • [9] Gupta R. D., Kundu D. Generalized exponential distribution: different method of estimations, Journal of Statistical Computation and Simulation, 69(4) (2001) 315-337.
  • [10] Kundu D., Raqab M. Z. Generalized Rayleigh distribution: different methods of estimations, Computational statistics & data analysis, 49(1) (2005) 187-200.
  • [11] Mazucheli J., Louzada F., Ghitany M. E. Comparison of estimation methods for the parameters of the weighted Lindley distribution, Applied Mathematics and Computation, 220 (2013) 463-471.
  • [12] Dey S., Dey T., Kundu D. Two-parameter Rayleigh distribution: different methods of estimation, American Journal of Mathematical and Management Sciences, 33(1) (2014) 55-74.
  • [13] Mohammadi K., Alavi O., Mostafaeipour A., Goudarzi N., Jalilvand M. Assessing different parameters estimation methods of Weibull distribution to compute wind power density, Energy Conversion and Management, 108 (2016) 322-335.
  • [14] Dey S., Zhang C., Asgharzadeh A., Ghorbannezhad M. Comparisons of methods of estimation for the NH distribution, Annals of Data Science, 4(4) (2017) 441-455.
  • [15] Shanker R. Sujatha distribution and its applications, Statistics in Transition-New series, 17(3) (2016) 391-410.
  • [16] Murthy D. N. P., Xie M., Jiang R. Weibull Models, New York: Wiley, (2004).
There are 16 citations in total.

Details

Primary Language English
Subjects Statistics
Journal Section Natural Sciences
Authors

Kadir Karakaya 0000-0002-0781-3587

Caner Tanış 0000-0003-0090-1661

Publication Date December 29, 2020
Submission Date July 7, 2020
Acceptance Date October 28, 2020
Published in Issue Year 2020

Cite

APA Karakaya, K., & Tanış, C. (2020). Different methods of estimation for the one parameter Akash distribution. Cumhuriyet Science Journal, 41(4), 944-950. https://doi.org/10.17776/csj.766011

Cited By

New Circular Distribution with an Application to Biology
Cumhuriyet Science Journal
https://doi.org/10.17776/csj.1316115
Parameters Estimation for the Unit log-log Distribution
Cumhuriyet Science Journal
https://doi.org/10.17776/csj.1171453
Modified-Lindley distribution and its applications to the real data
Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics
https://doi.org/10.31801/cfsuasmas.744141
An Alternative to the Marshall-Olkin Family of Distributions: Bootstrap, Regression and Applications
Communications on Applied Mathematics and Computation
https://doi.org/10.1007/s42967-021-00167-w
A COMPARISON OF ESTIMATION METHODS FOR ONE PARAMETER INVERSE GOMPERTZ DISTRIBUTION
Journal of Science and Arts
https://doi.org/10.46939/J.Sci.Arts-21.3-a06