(1) Publications
[1] Hirose K. and Masuda H.
Robust relative error estimation.
Entropy, 2018, 20(9), 632.
[2] Hirose, K. and Imada, M.
Sparse factor regression via penalized maximum likelihood estimation.
Statistical Papers, 59(2), 633–662, 2018.
[3] Dolinský, J., Hirose K. and Konishi, S.
Readouts for Echo-State Networks Built using Locally Regularized Orthogonal Forward Regression.
Journal of Applied Statistics, 45(4), 740-762, 2018.
[4] Hirose K., Fujisawa, H. and Sese, J.
Robust sparse Gaussian graphical modeling.
Journal of Multivariate Analysis, 161, 172-190, 2017.
open access
[5] Imada, M., Hirose, K., Yoshida, M., Sunyong, K., Toyozumi, N., Lopez, G. and Kano, Y.
An Interpersonal Sentiment Quantification method applied to Work Relationship Prediction.
NTT Technical Review 15(3), 2017.
[6] Yamamoto, M., Hirose, K., Nagata, H.
Graphical tool of sparse factor analysis.
Behaviormetrika, 44(1), 229-250, 2017.
[7] 廣瀬慧.
スパースモデリングとモデル選択.
電子情報通信学会誌, 99巻, 5号, 392-399項, 2016年.
PDFファイル
[8] Hirose, K., Kim, S., Kano, Y., Imada, M., Yoshida, M., and Matsuo, M.
Full information maximum likelihood estimation in factor analysis with a large number of missing values.
Journal of Statistical Computation and Simulation, 86(1), 91-104, 2016.
[9] Hirose, K.
Editorial: Recent advances in sparse statistical modeling.
Journal of the Japanese Society of Computational Statistics, 28, 51-52, 2015.
[10] Hirose, K., Ogura, Y. and Shimodaira, H.
Estimating Scale-Free Networks via the Exponentiation of Minimax Concave Penalty.
Journal of the Japanese Society of Computational Statistics, 28, 139-154, 2015.
[11] Hirose, K. and Yamamoto, M.
Sparse estimation via nonconcave penalized likelihood in a factor analysis model.
Statistics and Computing, 25(5), 863-875. 2015.
[12] Hirose, K. and Yamamoto, M.
Estimation of an oblique structure via penalized likelihood factor analysis.
Computational Statistics & Data Analysis, 79, 120-132. 2014.
[13] Hirose, K., Tateishi, S. and Konishi, S.
Tuning parameter selection in sparse regression modeling.
Computational Statistics & Data Analysis, 59, 28-40, 2013.
[14] Hirose, K., and Higuchi, T.
Creating facial animation of characters via MoCap data.
Journal of Applied Statistics, 39(12), 2583-2597, 2012.
[15] Hirose, K. and Konishi, S.
Variable selection via the weighted group lasso for factor analysis models.
The Canadian Journal of Statistics, 40(2), 345-361,2012.
[16] Hirose, K., Kawano, S., Konishi, S. and Ichikawa, M.
Bayesian information criterion and selection of the number of factors in factor analysis models.
Journal of Data Science, 9, 243-259, 2011.
[17] 川野秀一,廣瀬慧,立石正平,小西貞則.
回帰モデリングと L1型正則化法の最近の展開
日本統計学会誌.39巻,2号,211-242頁.2010年.
[18] Hirose, K., Kawano, S., Miike, D. and Konishi, S.
HYPER-PARAMETER SELECTION IN BAYESIAN STRUCTURAL EQUATION MODELS.
Bulletin of Informatics and Cybernetics, 42, 54-70, 2010.
[19] Hirose, K., Kawano, S. and Konishi, S.
BAYESIAN FACTOR ANALYSIS AND INFORMATION CRITERION.
Bulletin of Informatics and Cybernetics, 40, 75-87, 2008.
(2) Preprint
[1] Hirose K. and Terada Y.
Simple structure estimation via prenet penalization.
arXiv:1607.01145 (arXiv), 2016.