増田 弘毅 准教授(マス・フォア・インダストリ研究所)が，平成26年度日本統計学会研究業績賞を受賞
しました．ジャンプ型確率過程モデルの統計的漸近理論に関する以下の4編の論文が評価されたものです.

[1] Masuda, H. (2010), Approximate self-weighted LAD estimation of discretely observed ergodic Ornstein-Uhlenbeck processes. Electronic Journal of Statistics 4, 525-565.
http://dx.doi.org/10.1214/10-EJS565

[2] Kawai, R. and Masuda, H. (2013), Local asymptotic normality for normal inverse Gaussian Lévy processes with high-frequency sampling. ESAIM: Probability and Statistics 17, 13-32.
http://dx.doi.org/10.1051/ps/2011101

[3] Masuda, H. (2013), Asymptotics for functionals of self-normalized residuals of discretely observed stochastic processes. Stochastic Processes and their Applications 123, 2752-2778.
http://dx.doi.org/10.1016/j.spa.2013.03.013

[4] Masuda, H. (2013), Convergence of Gaussian quasi-likelihood random fields for ergodic Lévy driven SDE observed at high frequency. Annals of Statistics 41, 1593-1641.
http://dx.doi.org/10.1214/13-AOS1121

受賞対象業績：ジャンプ型確率過程モデルの統計解析に関する研究

日本統計学会平成26年度各賞受賞者Webpage
http://www.jss.gr.jp/ja/society/prize_biog.html#7