Non-Parametric Inference for Gini Covariance and its Variants
Document Type
Research Article
Publication Title
Sankhya A
Abstract
We obtain simple non-parametric estimators of Gini-based covariance, correlation and regression coefficients. We then establish the consistency and asymptotic normality of the proposed estimators. We provide an explicit formula for finding the asymptotic variance of the estimators. We also discuss jackknifed versions of the proposed estimators for reducing the bias of the estimators in case of small sample sizes. Finally, we evaluate the finite-sample performance of these estimators through on Monte Carlo simulations from a bivariate Pareto distribution. © 2020, Indian Statistical Institute.
First Page
1
Last Page
18
DOI
10.1007/s13171-020-00218-z
Publication Date
12-2020
Recommended Citation
Kattumannil, Sudheesh k.; Sreelakshmi, N; and Balakrishnan, N, "Non-Parametric Inference for Gini Covariance and its Variants" (2020). ISI Best Publications. 39.
https://digitalcommons.isical.ac.in/ibp/39
