Volume 44, Issue 1

January 2017

Including Special Features on “Recent Developments in Causal Discovery and Inference” and “Probabilistic Graphical Models and its Applications to Biomedical Informatics”

Issue Editors:

Shohei Shimizu,
Joe Suzuki,
Brandon Malone

17 articles in this issue

As the oldest journal of Data Science
Maomi Ueno
Editorial 26 December 2016 Pages: 1 - 2
Using R Package gesca for generalized structured component analysis
Sunmee Kim
Ramsey Cardwell
Heungsun Hwang
Note 30 November 2016 Pages: 3 - 23
Distribution-free properties of some asymptotic cumulants for the Mallows C _p and its modifications in usual and ridge regression
Haruhiko Ogasawara
Original Paper 07 December 2016 Pages: 25 - 56
A family of the adjusted estimators maximizing the asymptotic predictive expected log-likelihood
Haruhiko Ogasawara
Original Paper 09 December 2016 Pages: 57 - 95
A theoretical analysis of the BDeu scores in Bayesian network structure learning
Joe Suzuki
Original Paper 29 November 2016 Pages: 97 - 116
Emerging methods for conceptual modelling in neuroimaging
Hiroyuki Akama
Brian Murphy
Review Paper 19 December 2016 Pages: 117 - 133
Special feature: recent developments in causal discovery and inference
Shohei Shimizu
Preface 24 January 2017 Pages: 135 - 136
Causal feature learning: an overview
Krzysztof Chalupka
Frederick Eberhardt
Pietro Perona
Invited Paper 26 December 2016 Pages: 137 - 164
Methods for computational causal discovery in biomedicine
Sisi Ma
Alexander Statnikov
Invited Paper 20 January 2017 Pages: 165 - 191
Causal search procedures for fMRI: review and suggestions
Teague Henry
Kathleen Gates
Invited Paper 20 December 2016 Pages: 193 - 225
Special feature: probabilistic graphical models and its applications to biomedical informatics—part 1
Joe Suzuki
Brandon Malone
Preface 30 January 2017 Pages: 227 - 228
Graphical tool of sparse factor analysis
Michio Yamamoto
Kei Hirose
Haruhisa Nagata
Invited Paper 04 January 2017 Pages: 229 - 250
Erratum to: Graphical tool of sparse factor analysis
Michio Yamamoto
Kei Hirose
Haruhisa Nagata
Erratum 18 February 2017 Pages: 251 - 251
A global goodness-of-fit test for linear structural mean models
Masataka Taguri
Shizue Izumi
Invited Paper Open access 30 November 2016 Pages: 253 - 262
Erratum to: A global goodness-of-fit test for linear structural mean models
Masataka Taguri
Shizue Izumi
Erratum 16 January 2017 Pages: 263 - 263
Learning sparse structural changes in high-dimensional Markov networks
Song Liu
Kenji Fukumizu
Taiji Suzuki
Invited Paper Open access 13 February 2017 Pages: 265 - 286
Structural learning of causal networks
Yangbo He
Jinzhu Jia
Zhi Geng
Invited Paper 14 February 2017 Pages: 287 - 305

Volume 44, Issue 1

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