Volume 18, Issue 2, June 2019, Pages 113 - 122
Divergence Measures Estimation and Its Asymptotic Normality Theory Using Wavelets Empirical Processes III
Authors
Amadou Diadié Bâ1, Gane Samb Lo2, *, Diam Bâ3
1Unité de Formation et de Recherche des Sciences Appliquées à la Technologie, Laboratoire d'Etudes et de Recherches en Statistiques et Développement, Gaston Berger University, Saint Louis, Sénégal
2LERSTAD, Gaston Berger University, Saint-Louis, Senegal, Evanston Drive, NW, Calgary, Canada, T3P 0J9, Associate Researcher, LSTA, Pierre et Marie University, Paris, France, Associated Professor, African University of Sciences and Technology, Abuja, Nigeria
3Unité de Formation et de Recherche des Sciences Appliquées à la Technologie, Laboratoire d'Etudes et de Recherches en Statistiques et Développement, Gaston Berger University, Saint Louis, Sénégal
*Corresponding author. Email: gane-samb.lo@ugb.edu.sn
Corresponding Author
Gane Samb Lo
Received 29 October 2018, Accepted 24 February 2019, Available Online 23 May 2019.
- DOI
- 10.2991/jsta.d.190514.002How to use a DOI?
- Keywords
- Divergence measures estimation
- Abstract
In the two previous papers of this series, the main results on the asymptotic behaviors of empirical divergence measures based on wavelets theory have been established and particularized for important families of divergence measures like Rényi and Tsallis families and for the Kullback-Leibler measures. While the proofs of the results in the second paper may be skipped, the proofs of those in paper 1 are to be thoroughly proved since they serve as a foundation to the whole structure of results. We prove them in this last paper of the series. We will also address the applicability of the results to usual distribution functions.
- Copyright
- © 2019 The Authors. Published by Atlantis Press SARL.
- Open Access
- This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).
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TY - JOUR AU - Amadou Diadié Bâ AU - Gane Samb Lo AU - Diam Bâ PY - 2019 DA - 2019/05/23 TI - Divergence Measures Estimation and Its Asymptotic Normality Theory Using Wavelets Empirical Processes III JO - Journal of Statistical Theory and Applications SP - 113 EP - 122 VL - 18 IS - 2 SN - 2214-1766 UR - https://doi.org/10.2991/jsta.d.190514.002 DO - 10.2991/jsta.d.190514.002 ID - Bâ2019 ER -