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Widely used income inequality measure, Gini index is extended to form a family of income inequality measures known as Single-Series Gini (S-Gini) indices. In this study, we develop empirical likelihood (EL) and jackknife empirical…

Methodology · Statistics 2024-05-29 Sreelakshmi N , Sudheesh K Kattumannil , Rituparna Sen

We develop a jackknife empirical likelihood (JEL) framework for inference on parameters defined through multivariate three-sample U-statistic. From three independent multivariate samples, we construct JEL ratio statistic based on suitable…

Methodology · Statistics 2025-12-03 Naresh Garg , Litty Mathew , Isha Dewan , Sudheesh Kumar Kattumannil

In this paper, a frequency coefficient based on the Sen-Shorrocks-Thon (SST) poverty index notion is proposed. The clustering SST index can be used as the method for determination of the connection between similar neighbor sub-clusters.…

Machine Learning · Statistics 2017-10-26 Lukas Pastorek

A new measure of income inequality that captures the heavy tail behavior of the income distribution is proposed. We discuss two different approaches to find the estimators of the proposed measure. We show that these estimators are…

Methodology · Statistics 2024-08-21 Sudheesh K Kattumannil , Saparya Suresh

The categorical Gini correlation, $\rho_g$, was proposed by Dang et al. to measure the dependence between a categorical variable, $Y$ , and a numerical variable, $X$. It has been shown that $\rho_g$ has more appealing properties than…

Methodology · Statistics 2023-10-17 Sameera Hewage , Yongli Sang

In the present article, we discuss jackknife empirical likelihood (JEL) and adjusted jackknife empirical likelihood (AJEL) based inference for finding confidence intervals for probability weighted moment (PWM). We obtain the asymptotic…

Methodology · Statistics 2018-07-13 Deepesh Bhati , Sudheesh K Kattumannil , N Sreelakshmi

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…

Methodology · Statistics 2024-02-29 Saparya Suresh , Sudheesh K. Kattumannil

In many applications, parameters of interest are estimated by solving some non-smooth estimating equations with $U$-statistic structure. Jackknife empirical likelihood (JEL) approach can solve this problem efficiently by reducing the…

Methodology · Statistics 2019-06-18 Yongli Sang , Xin Dang , Yichuan Zhao

Jackknife empirical likelihood (JEL) is an effective modified version of empirical likelihood method (EL). Through the construction of the jackknife pseudo-values, JEL overcomes the computational difficulty of EL method when its constraints…

Methodology · Statistics 2016-03-15 Ying-Ju Chen , Wei Ning

Survival extropy, which quantifies the uncertainty associated with the remaining lifetime distribution, provides an information-theoretic perspective on survival behavior. We consider a divergence measure based on survival extropy and…

Statistics Theory · Mathematics 2025-12-03 Naresh Garg , Isha Dewan , Sudheesh Kumar Kattumannil

In the present article, we propose jackknife empirical likelihood (JEL) ratio test for testing the independence of time to failure and cause of failure in competing risks data. We use U-statistic theory to derive the JEL ratio test. The…

Methodology · Statistics 2021-10-19 Sreelakshmy N. , Sreedevi E. P

We develop an empirical likelihood (EL) framework for random forests and related ensemble methods, providing a likelihood-based approach to quantify their statistical uncertainty. Exploiting the incomplete $U$-statistic structure inherent…

Machine Learning · Statistics 2025-11-19 Harold D. Chiang , Yukitoshi Matsushita , Taisuke Otsu

Abundance estimation from capture-recapture data is of great importance in many disciplines. Analysis of capture-recapture data is often complicated by the existence of one-inflation and heterogeneity problems. Simultaneously taking these…

Methodology · Statistics 2025-07-15 Yang Liu , Pengfei Li , Yukun Liu , Riquan Zhang

Demand for reliable statistics at a local area (small area) level has greatly increased in recent years. Traditional area-specific estimators based on probability samples are not adequate because of small sample size or even zero sample…

Methodology · Statistics 2023-06-09 Maryam Sohrabi , J. N. K. Rao

We propose the so-called jackknife empirical likelihood approach for the survey data of general unequal probability sampling designs, and analyze parameters defined according to U-statistics. We prove theoretically that jackknife…

Methodology · Statistics 2023-03-28 Mengdong Shang , Xia Chen

The Gini correlation plays an important role in measuring dependence of random variables with heavy tailed distributions, whose properties are a mixture of Pearson's and Spearman's correlations. Due to the structure of this dependence…

Methodology · Statistics 2018-06-05 Yongli Sang , Xin Dang , Yichuan Zhao

Empirical likelihood is a well-known nonparametric method in statistics and has been widely applied in statistical inference. The method has been employed by Lu and Peng (2002) to constructing confidence intervals for the tail index of a…

Methodology · Statistics 2019-04-19 Yizeng Li , Yongcheng Qi

Sequential trial emulation (STE) is an approach to estimating causal treatment effects by emulating a sequence of target trials from observational data. In STE, inverse probability weighting is commonly utilised to address time-varying…

Methodology · Statistics 2025-07-10 Juliette M. Limozin , Shaun R. Seaman , Li Su

The area under a receiver operating characteristic curve (AUC) is a useful tool to assess the performance of continuous-scale diagnostic tests on binary classification. In this article, we propose an empirical likelihood (EL) method to…

Methodology · Statistics 2022-05-05 Chul Moon , Xinlei Wang , Johan Lim

Generalized partially linear single-index models (GPLSIMs) provide a flexible and interpretable semiparametric framework for longitudinal outcomes by combining a low-dimensional parametric component with a nonparametric index component. For…

Methodology · Statistics 2026-02-19 Tianni Zhang , Yuyao Wang , Yu Lu , Mengfei Ran
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