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Journal of Nonparametric Statistics Volume 27, 2015 - Issue 1
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Original Articles

Family of the generalised gamma kernels: a generator of asymmetric kernels for nonnegative data

Masayuki HirukawaFaculty of Economics, Setsunan University, 17-8 Ikeda Nakamachi, Neyagawa, Osaka572-8508, JapanCorrespondence[email protected]
&
Mari SakudoResearch Institute of Capital Formation, Development Bank of Japan, 9-7, Otemachi 1-chome, Chiyoda-ku, Tokyo100-8178, Japan
Pages 41-63 | Received 19 Jun 2013, Accepted 25 Nov 2014, Published online: 28 Jan 2015

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Sobom M. Somé. (2022) Bayesian selector of adaptive bandwidth for gamma kernel density estimator on simulations and applications. Communications in Statistics - Simulation and Computation 51:12, pages 7287-7297.
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Sobom M. Somé & Célestin C. Kokonendji. (2022) Bayesian selector of adaptive bandwidth for multivariate gamma kernel estimator on [0,∞ ). Journal of Applied Statistics 49:7, pages 1692-1713.
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Kahina Bedouhene & Nabil Zougab. (2022) Nonparametric multiplicative bias correction for von Mises kernel circular density estimator. Communications in Statistics - Simulation and Computation 51:3, pages 774-792.
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L. Harfouche, N. Zougab, S. Adjabi & B. Funke. (2022) Discrete multivariate associated kernel estimators using two multiplicative bias correction methods. Communications in Statistics - Simulation and Computation 51:2, pages 404-420.
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S. Makhloufi, N. Zougab, Y. Ziane & S. Adjabi. (2021) A family of asymmetric kernels based on log-symmetric distributions. Communications in Statistics - Simulation and Computation 0:0, pages 1-18.
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Gaku Igarashi & Yoshihide Kakizawa. (2020) Higher-order bias corrections for kernel type density estimators on the unit or semi-infinite interval. Journal of Nonparametric Statistics 32:3, pages 617-647.
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Gaku Igarashi & Yoshihide Kakizawa. (2018) Limiting bias-reduced Amoroso kernel density estimators for non-negative data. Communications in Statistics - Theory and Methods 47:20, pages 4905-4937.
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Gery Geenens & Craig Wang. (2018) Local-Likelihood Transformation Kernel Density Estimation for Positive Random Variables. Journal of Computational and Graphical Statistics 27:4, pages 822-835.
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N. Zougab, L. Harfouche, Y. Ziane & S. Adjabi. (2018) Multivariate generalized Birnbaum—Saunders kernel density estimators. Communications in Statistics - Theory and Methods 47:18, pages 4534-4555.
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Gaku Igarashi & Yoshihide Kakizawa. (2018) Generalised gamma kernel density estimation for nonnegative data and its bias reduction. Journal of Nonparametric Statistics 30:3, pages 598-639.
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Articles from other publishers (21)

Libaud Rudy Aurelien Doho, Sobom Matthieu Somé & Jean Michel Banto. (2023) Inflation and west African sectoral stock price indices: An asymmetric kernel method analysis. Emerging Markets Review 54, pages 100987.
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Sobom M. Somé, Célestin C. Kokonendji, Smail Adjabi, Naushad A. Mamode Khan & Said Beddek. (2023) Multiple combined gamma kernel estimations for nonnegative data with Bayesian adaptive bandwidths. Computational Statistics.
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Frédéric Ouimet. (2022) A symmetric matrix-variate normal local approximation for the Wishart distribution and some applications. Journal of Multivariate Analysis 189, pages 104923.
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Yoshihide Kakizawa. (2022) Multivariate elliptical-based Birnbaum–Saunders kernel density estimation for nonnegative data. Journal of Multivariate Analysis 187, pages 104834.
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Frédéric Ouimet & Raimon Tolosana-Delgado. (2022) Asymptotic properties of Dirichlet kernel density estimators. Journal of Multivariate Analysis 187, pages 104832.
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Benedikt Funke & Masayuki Hirukawa. (2021) Bias correction for local linear regression estimation using asymmetric kernels via the skewing method. Econometrics and Statistics 20, pages 109-130.
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Gery Geenens. (2020) Mellin–Meijer kernel density estimation on $${{\mathbb {R}}}^+$$. Annals of the Institute of Statistical Mathematics 73:5, pages 953-977.
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Yoshihide Kakizawa. (2021) A class of Birnbaum–Saunders type kernel density estimators for nonnegative data. Computational Statistics & Data Analysis 161, pages 107249.
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Célestin C. Kokonendji & Sobom M. Somé. (2021) Bayesian Bandwidths in Semiparametric Modelling for Nonnegative Orthant Data with Diagnostics. Stats 4:1, pages 162-183.
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Yoshihide Kakizawa. (2020) Multivariate non-central Birnbaum–Saunders kernel density estimator for nonnegative data. Journal of Statistical Planning and Inference 209, pages 187-207.
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Gaku Igarashi & Yoshihide Kakizawa. (2020) Multiplicative bias correction for asymmetric kernel density estimators revisited. Computational Statistics & Data Analysis 141, pages 40-61.
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Masayuki Hirukawa & Mari Sakudo. (2019) Another bias correction for asymmetric kernel density estimation with a parametric start. Statistics & Probability Letters 145, pages 158-165.
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Benedikt Funke & Masayuki Hirukawa. (2019) Nonparametric estimation and testing on discontinuity of positive supported densities: a kernel truncation approach. Econometrics and Statistics 9, pages 156-170.
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Lynda Harfouche, Smail Adjabi, Nabil Zougab & Benedikt Funke. (2017) Multiplicative bias correction for discrete kernels. Statistical Methods & Applications 27:2, pages 253-276.
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Mariusz Grządziel. (2018) On using nonparametric approaches for precipitation estimation. ITM Web of Conferences 23, pages 00013.
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Masayuki HirukawaMasayuki Hirukawa. 2018. Asymmetric Kernel Smoothing. Asymmetric Kernel Smoothing 41 58 .
Masayuki HirukawaMasayuki Hirukawa. 2018. Asymmetric Kernel Smoothing. Asymmetric Kernel Smoothing 17 39 .
Masayuki HirukawaMasayuki Hirukawa. 2018. Asymmetric Kernel Smoothing. Asymmetric Kernel Smoothing 1 15 .
Yoshihide Kakizawa & Gaku Igarashi. (2017) Inverse gamma kernel density estimation for nonnegative data. Journal of the Korean Statistical Society 46:2, pages 194-207.
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Masayuki Hirukawa & Mari Sakudo. (2016) Testing Symmetry of Unknown Densities via Smoothing with the Generalized Gamma Kernels. Econometrics 4:4, pages 28.
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Benedikt Funke & Rafael Kawka. (2015) Nonparametric density estimation for multivariate bounded data using two non-negative multiplicative bias correction methods. Computational Statistics & Data Analysis 92, pages 148-162.
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