Kanta Naito

452 total citations
51 papers, 278 citations indexed

About

Kanta Naito is a scholar working on Statistics and Probability, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Kanta Naito has authored 51 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 9 papers in Artificial Intelligence and 6 papers in Electrical and Electronic Engineering. Recurrent topics in Kanta Naito's work include Statistical Methods and Inference (29 papers), Advanced Statistical Methods and Models (23 papers) and Bayesian Methods and Mixture Models (9 papers). Kanta Naito is often cited by papers focused on Statistical Methods and Inference (29 papers), Advanced Statistical Methods and Models (23 papers) and Bayesian Methods and Mixture Models (9 papers). Kanta Naito collaborates with scholars based in Japan, Australia and United States. Kanta Naito's co-authors include Inge Koch, Yasunori Fujikoshi, Lixing Zhu, H. Inaba, Jun Udagawa, Hiroki Otani, Yuki Saito, T Nagao, S Harigaya and Hidemitsu Nakajima and has published in prestigious journals such as Statistics in Medicine, The Annals of Statistics and Machine Learning.

In The Last Decade

Kanta Naito

43 papers receiving 257 citations

Peers

Countries citing papers authored by Kanta Naito

Since Specialization

Citations

This map shows the geographic impact of Kanta Naito's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kanta Naito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanta Naito more than expected).

Fields of papers citing papers by Kanta Naito

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kanta Naito. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kanta Naito. The network helps show where Kanta Naito may publish in the future.

Co-authorship network of co-authors of Kanta Naito

This figure shows the co-authorship network connecting the top 25 collaborators of Kanta Naito. A scholar is included among the top collaborators of Kanta Naito based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kanta Naito. Kanta Naito is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Semiparametric density estimation with localized Bregman divergence 2025 ·Journal of Multivariate Analysis ·(unknown), Kanta Naito	0
2	Robustness of Principal Component Analysis with Spearman’s Rank Matrix 2024 ·Journal of Statistical Theory and Practice ·(unknown), Kanta Naito, Inge Koch	0
3	Kernel density estimation by stagewise algorithm with a simple dictionary 2022 ·Computational Statistics ·(unknown), Kanta Naito	2
4	Regression using localised functional Bregman divergence 2021 ·Electronic Journal of Statistics ·Kanta Naito, Spiridon Penev	0
5	Asymptotics and practical aspects of testing normality with kernel methods 2020 ·Journal of Multivariate Analysis ·(unknown), Kanta Naito	0
6	Asymptotic theory for local estimators based on Bregman divergence 2019 ·Canadian Journal of Statistics ·(unknown), Kanta Naito	1
7	Locally robust methods and near-parametric asymptotics 2018 ·Journal of Multivariate Analysis ·Spiridon Penev, Kanta Naito	2
8	Statistical analyses in trials for the comprehensive understanding of organogenesis and histogenesis in humans and mice 2016 ·The Journal of Biochemistry ·Hiroki Otani, Jun Udagawa, Kanta Naito	6
9	Pattern recognition based on canonical correlations in a high dimension low sample size context 2012 ·Journal of Multivariate Analysis ·(unknown), Inge Koch, Kanta Naito	4
10	Boosting for density estimation based on U loss function 2010 ·IEICE Technical Report; IEICE Tech. Rep. ·Osamu Komori, Kanta Naito, Shinto Eguchi	1
11	Analysis of the harmonized growth pattern of fetal organs by multidimensional scaling and hierarchical clustering 2010 ·Congenital Anomalies ·Jun Udagawa, Akira Yasuda, Kanta Naito, Hiroki Otani	8
12	Multidimensional standard curve for the development process of human fetuses 2010 ·Statistics in Medicine ·Kanta Naito, Jun Udagawa, Hiroki Otani	4
13	Bandwidth selection for a data sharpening estimator in nonparametric regression 2009 ·Journal of Multivariate Analysis ·Kanta Naito, (unknown)	2
14	Non-parametric kernel regression for multinomial data 2006 ·Journal of Multivariate Analysis ·(unknown), Kanta Naito	7
15	Weighted kernel estimators in nonparametric binomial regression 2004 ·Journal of nonparametric statistics ·(unknown), Kanta Naito	16
16	Semiparametric density estimation by local L2-fitting 2004 ·The Annals of Statistics ·Kanta Naito	22
17	Practical Aspects of Bias Reducing Estimators in Nonparametric Regression 2004 ·(unknown), Kanta Naito	0
18	On a certain class of nonparametric density estimators with reduced bias 2001 ·Statistics & Probability Letters ·Kanta Naito	4
19	Approximation of the Power of Kurtosis Test for Multinormality 1998 ·Journal of Multivariate Analysis ·Kanta Naito	2
20	On weighting the studentized empirical characteristic function for testing normality 1996 ·Communications in Statistics - Simulation and Computation ·Kanta Naito	8

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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