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Jackknife empirical likelihood ratio test for testing the equality of semivariance
Publication type: Journal Article
Publication date: 2024-12-12
scimago Q2
wos Q3
SJR: 0.775
CiteScore: 2.3
Impact factor: 1.1
ISSN: 09325026, 16139798
Abstract
Semivariance is a measure of the dispersion of all observations that fall above the mean or target value of a random variable and it plays an important role in life-length, actuarial and income studies. In this paper, we develop a new non-parametric test for testing the equality of upper semivariance. We use the U-statistic theory to derive the test statistic and then study the asymptotic properties of the test statistic. We also develop a jackknife empirical likelihood (JEL) ratio test for testing the equality of upper semivariance. Extensive Monte Carlo simulation studies are carried out to validate the performance of the proposed JEL-based test. We illustrate the test procedure using real data.
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Citations from 2024:
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Suresh S. et al. Jackknife empirical likelihood ratio test for testing the equality of semivariance // Statistical Papers. 2024. Vol. 66. No. 1. 16
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Suresh S., Kattumannil S. K. Jackknife empirical likelihood ratio test for testing the equality of semivariance // Statistical Papers. 2024. Vol. 66. No. 1. 16
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TY - JOUR
DO - 10.1007/s00362-024-01636-z
UR - https://link.springer.com/10.1007/s00362-024-01636-z
TI - Jackknife empirical likelihood ratio test for testing the equality of semivariance
T2 - Statistical Papers
AU - Suresh, Saparya
AU - Kattumannil, Sudheesh K
PY - 2024
DA - 2024/12/12
PB - Springer Nature
IS - 1
VL - 66
SN - 0932-5026
SN - 1613-9798
ER -
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@article{2024_Suresh,
author = {Saparya Suresh and Sudheesh K Kattumannil},
title = {Jackknife empirical likelihood ratio test for testing the equality of semivariance},
journal = {Statistical Papers},
year = {2024},
volume = {66},
publisher = {Springer Nature},
month = {dec},
url = {https://link.springer.com/10.1007/s00362-024-01636-z},
number = {1},
pages = {16},
doi = {10.1007/s00362-024-01636-z}
}
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