Year 2021, Volume , Issue 34, Pages 72 - 81 2021-03-30

On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation

Caner TANIŞ [1]


Transmuted power function distribution is generated using the quadratic rank transmutation method based on the mixture of the distributions of two order statistics. The distributions generating via Quadratic rank transmutation map are more flexible than the baseline ones since they have a potential to model various dataset. In this study, we provide some distributional properties and statistical inferences of transmuted power function distribution. We describe several previously unexamined properties, such as density shape, hazard shape, and the transmuted power function distribution measures. We also tackle the problem of point estimation for transmuted power function distribution. In this regard, maximum likelihood, least-squares, weighted least-squares, Anderson-Darling method, and Crámer–Von-Mises method are considered to estimate the two parameters of transmuted power function distribution. A comprehensive Monte Carlo simulation study is performed to compare these methods via bias and mean-squared errors.
Transmuted power function distribution, power function distribution, point estimation, risk measures, Monte Carlo simulation
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Primary Language en
Subjects Mathematics, Mathematics, Interdisciplinary Applications
Journal Section Research Article
Authors

Orcid: 0000-0003-0090-1661
Author: Caner TANIŞ (Primary Author)
Institution: CANKIRI KARATEKIN UNIVERSITY
Country: Turkey


Dates

Publication Date : March 30, 2021

Bibtex @research article { jnt878386, journal = {Journal of New Theory}, issn = {}, eissn = {2149-1402}, address = {Mathematics Department, Gaziosmanpasa University 60250 Tokat-TURKEY.}, publisher = {Gaziosmanpasa University}, year = {2021}, volume = {}, pages = {72 - 81}, doi = {}, title = {On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation}, key = {cite}, author = {Tanış, Caner} }
APA Tanış, C . (2021). On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation . Journal of New Theory , (34) , 72-81 . Retrieved from https://dergipark.org.tr/en/pub/jnt/issue/61070/878386
MLA Tanış, C . "On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation" . Journal of New Theory (2021 ): 72-81 <https://dergipark.org.tr/en/pub/jnt/issue/61070/878386>
Chicago Tanış, C . "On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation". Journal of New Theory (2021 ): 72-81
RIS TY - JOUR T1 - On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation AU - Caner Tanış Y1 - 2021 PY - 2021 N1 - DO - T2 - Journal of New Theory JF - Journal JO - JOR SP - 72 EP - 81 VL - IS - 34 SN - -2149-1402 M3 - UR - Y2 - 2021 ER -
EndNote %0 Journal of New Theory On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation %A Caner Tanış %T On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation %D 2021 %J Journal of New Theory %P -2149-1402 %V %N 34 %R %U
ISNAD Tanış, Caner . "On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation". Journal of New Theory / 34 (March 2021): 72-81 .
AMA Tanış C . On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation. JNT. 2021; (34): 72-81.
Vancouver Tanış C . On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation. Journal of New Theory. 2021; (34): 72-81.
IEEE C. Tanış , "On Transmuted Power Function Distribution: Characterization, Risk Measures, and Estimation", Journal of New Theory, no. 34, pp. 72-81, Mar. 2021