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Statistics | Behaviormetrika (Editorial Board)

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Editor-in-Chief: Maomi Ueno

ISSN: 0385-7417 (print version)
ISSN: 1349-6964 (electronic version)

Journal no. 41237

Maomi Ueno

Coordinating Editors
Heungsun Hwang
Shuichi Kawano
Brandon Malone
Minoru Nakayama
Akinori Okada
Marko Sarstedt
Ronny Scherer
Kazuo Shigemasu
Shohei Shimizu
Joe Suzuki
Wim J. van der Linden
Marie Wiberg

Advisory Board
Kohei Adachi
Hans-Hermann Bock
Ulf Bockenholt
Wray Buntine   
Włodzisław Duch  
Wolfgang Gaul
Patrick Groenen 
Willem J. Heiser
Aapo Hyvarinen
Yutaka Kano
Thomas Richardson
Michael Smithson
Michael E. Sobel
Yoshio Takane
Ben Tatler
Iven Van Mechelen
Maurizio Vichi
Ke-Hai Yuan

Associate Editors
Russell G. Almond
Daniel Baier
Abdelhadi Bellachhab
Giuseppe Bove
Hamparsum Bozdogan
Theodore Chadjipadelis
Andrzej Cichocki
Mark de Rooij
Reinhold Decker
Zhi Geng
Michael Gutmann
Kei Hirose
Yili Hong
Takahiro Hoshino
Jukka Huhtamäki
Antti Hyttinen
Wolfgang Jagodzinski 
Kentaro Kato
Manabu Kuroki 
Berthold Lausen
Urbano Lorenzo-Seva
Yasuo Miyazaki
Alessio Moneta
Fiona Mulvey        
Haruhiko Ogasawara
Kensuke Okada
Thomas Pederson 
Matthew Purver
Teemu Roos
Neil Rubens
Marcus Selart
Ricardo Silva
Kazuhisa Takemura
Javier Trejos Zelaya
Michel van de Velden
Donatella Vicari
Kazuho Watanabe   
Wolfgang Wiedermann
Michio Yamamoto
Hirokazu Yanagihara
Helen Yannakoudakis
Hsiu-Ting Yu
Kun Zhang
Jiji Zhang

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  • Aims and Scope

    Aims and Scope


    Behaviormetrika is issued twice a year to provide an international forum for new theoretical and empirical quantitative approaches in data science. When Behaviormetrika was launched in 1974, the journal advocated data science, as an interdisciplinary field that included the use of statistical methods to extract meaningful knowledge from data in its various forms: structured or unstructured. Behaviormetrika is the oldest journal addressing the topic of data science. The first editor-in-chief of Behaviormetrika, Dr. Chikio Hayashi, described data science in this way:

    “Data science is not only a synthetic concept to unify statistics, data analysis, and their related methods; it also comprises its results. Data science is intended to analyze and understand actual phenomena with ‘data.’ In other words, the aim of data science is to reveal the features or the hidden structure of complicated natural, human, and social phenomena using data from a different perspective from the established or traditional theory and method.”  

    Behaviormetrika is a fully refereed international journal, which publishes original research papers, notes, and review articles. Subject areas suitable for publication include but are not limited to the following methodologies and fields. 


    -Data science

    -Mathematical statistics

    -Survey methodologies

    -Artificial intelligence

    -Information theory

    -Machine learning

    -Knowledge discovery in databases (KDD)

    -Graphical models

    -Computer science









    -Social science


    -Political science

    -Policy science

    -Cognitive science

    -Brain science

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    Instructions for Authors


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