西山陽一のウェッブページ
(Web page for Yoichi Nishiyama)

（April 27th, 2010，統計数理研究所編集室・Ｗさん撮影)



著書 「マルチンゲール理論による統計解析」　近代科学社　ＩＳＭシリーズ：進化する統計数理１　が２０１１年１０月刊行，発売中！です

内容紹介：条件付き期待値の直観的説明から始め，任意抽出定理の使用上の注意，伊藤の公式とは何であるか，マルチンゲール中心極限定理の証明などを統計ユーザーの立場から解説しています．
しかる後に，漸近理論のためのツールをまとめ，それを用いて確率過程の推定問題を統一的手法により見通しよく扱っています．和書はもちろん，洋書にも類書は見あたらないと思います．

[まえがきと目次]　[近代科学社ブックストアのページ, Amazon のページ]　[正誤表]

〒190-8562 東京都立川市緑町 10-3
統計数理研究所
准教授

Associate Professor
The Institute of Statistical Mathematics
10-3 Midori-cho, Tachikawa, Tokyo 190-8562, Japan

Email: nisiyama

To ISM official page

Research Theme: Entropy Methods and Martingales, with Applications to Statistics

• Theory and statistical applications of random fields. (Keywords: maximal inequality, weak convergence theorem, unifrom central limit theorem, B(T)-space, Hilbert space, metric entropy, bracketing entropy, Donsker class, invariance principle.)
• Statistical inference for stochastic processes. (Keywords: semimartingale, diffusion process, counting process, Levy process, non-linear time series, multiplicative intensity model, Cox regression, discrete sampling.)
• Semi- and non-parametric statistical inference. (Keywords: local asymptotic normality, asymptotic efficiency, rate of convergence, M-estimator, Z-estimator, Bayes estimator, kernel estimator, projection estimator, Nelson-Aalen estimator, infinite-dimensional nuisance parameter, goodness-of-fit test, two sample problem, change point problem.)
• Application fields include survival analysis and mathematical finance.

Information

• Associate Editor of: Ann. Inst. Statist. Math. (2008-), J. Japan Statist. Soc. (2010-).
• Local Organizing Comittee of 2nd Institute of Mathematical Statistics Asia Pacific Rim Meeting 2012, which will be held from 1st to 4th July, 2012, in Tsukuba. [Web page]
• 平成２３年１１月１０日（木）〜１１日（金）に，公開講座「マルチンゲール理論による統計解析の基礎」を実施しました．受講者は５３名でした．[シラバス, 受講者からの声]
• 他の（主として実施済みの）情報へのリンク
  

Profile ( Official [Japanese,English], Informal [Japanese] )

Awards

• 第２３回日本統計学会小川研究奨励賞（2009年9月）
  • Richard D. Gill 教授による「受賞者紹介」と西山による「受賞のことば」が掲載された会報 No.141 はこちら．
  • 平成２２年３月７日に青山学院大学にて開催された日本統計学会春季集会 2010 における講演のスライドはこちら．

Light Readings

• Donser の不変原理と確率過程のノンパラメトリック推測 (ISM News No. 96 掲載, 2007 年)
• ISM と IMS (ISM News No. 109 掲載, 2010 年)
• 確率過程の統計的推測のための「無限次元」研究 (ISM News No.112 掲載, 2011 年)

Slides for Recent Talks

• 変化点問題，丸められたデータの問題 (統計数理セミナー，2011年4月13日)
  

Links

Ｌｅｃｔｕｒes (2010-)

• 平成２３年度後期（短期集中）：大阪府立大学理学系研究科情報数理科学専攻「確率過程特論」 [シラバス]
• 平成２３年度前期：早稲田大学基幹理工学部応用数理学科「確率と確率過程Ａ」 [Web page]
• 平成２２年度後期：総合研究大学院大学複合科学研究科統計科学専攻「推測数理概論II」 [Web page]
  

Oral Presentation (2006-)

• April 2012 - March 2013
• April 2011 - March 2012
• April 2010 - March 2011
• April 2009 - March 2010
• April 2008 - March 2009
• April 2007 - March 2008
• April 2006 - March 2007
  

Recent Papers (If you want a copy, send email to nisiyama)

注意：　この欄は，ファースト・ヴァージョンが完成した日付の新しい順に並んでいます．月が入っているものは今後の改訂の可能性があります．月が入っていないものは確定版で，この場合の年号は出版年または（非出版の場合には）最終版の執筆年です．

• 西山陽一 (January 2012). ノンパラメトリック変化点問題に対する順位統計量について. Submitted for publication.
• Nishiyama, Y. (May 2011). Adaptive semiparametric Bayes estimation. Research Memorandum 1141, Inst. Statist. Math.
• Nishiyama, Y. (March 2011). A martingale central limit theorem in Hilbert space and change point problems for diffusion processes. Research Memorandum 1140, Inst. Statist. Math.
• Nishiyama, Y. (2011). A rank statistic for non-parametric k-sample and change point problems. J. Japan Statist. Soc. 41 67-73.
• Fujii, T. and Nishiyama, Y. (February 2011). Testing for parameter change in a stress release process. Submitted for publication.
• Negri, I. and Nishiyama, Y. (201?). Asymptotically distribution free test for parameter change in a diffusion process model. To appear in Ann. Inst. Statist. Math.
• Nishiyama, Y. (2011). An asymptotically distribution free test for non-parametric change point problem. Research Memorandum 1132, Inst. Statist. Math.
• Nishiyama, Y. (2010). Asymptotically distribution free test for parameter change. Research Memorandum 1130, Inst. Statist. Math.
• Fujii, T. and Nishiyama, Y. (201?). Some problems in nonparametric inference for the stress release process related to the local time. To appear in Ann. Inst. Statist. Math..
• Nishiyama, Y. (2010). Goodness-of-fit tests for ergodic Markov chains as clean applications of infinite-dimensional martingale central limit theorems. Revised version of Research Memorandum 1126, Inst. Statist. Math.
• Negri, I. and Nishiyama, Y. (2010). Review on goodness of fit tests for ergodic diffusion processes by different sampling schemes. Economic Notes. 39 91-106.
• 西山陽一 (2010). 平滑化 Nelson-Aalen 推定量の一様収束率. 統計数理 58 131-135.
• 西山陽一 (2010). 射影推定量についての一注意. 統計数理 58 127-130.
• Nishiyama, Y. (February 2010). A martingale central limit theorem in Hilbert space and its applications. Research Memorandum 1116, Inst. Statist. Math.
• Nishiyama, Y. (2009). Two sample problem for rounded data. J. Japan Statist. Soc. 39 233-238.
• Nishiyama, Y. (2011). Estimation for the invariant law of an ergodic diffusion process based on high-frequency data. J. Nonparametr. Statist. 23 909-915.
• Negri, I. and Nishiyama, Y. (2010). Goodness of fit test for ergodic diffusions by tick time sample scheme. Stat. Inference Stoch. Process. 13 81-95.
• Nishiyama, Y. (2009). Two sample test for counting processes with a non-linear covariate based on smoothed empirical processes. Research Memorandum 1095, Inst. Statist. Math.
• Nishiyama, Y. (2009). Goodness-of-fit test for a nonlinear time series. J. Time Ser. Anal. 30 674-681. Corrigendum (2010) 31 227.
• Nishiyama, Y. (2009). Parametric estimation for volatility of ergodic diffusion process with unspecified drift. A revised version of Research Memorandum 1093, Inst. Statist. Math. [pdf]
• Nishiyama, Y. (2011). On Z-estimation by rounded data. J. Statist. Plann. Inference 141 287-292.
• Nishiyama, Y. (2009). Two sample test for diffusion processes with a non-linear covariate. Research Memorandum 1090, Inst. Statist. Math. [pdf]
• Nishiyama, Y. (2009). A note on semiparametric estimation for ergodic diffusion processes. Manuscritpｔ. [pdf]
• Nishiyama, Y. (2011). Impossibility of weak convergence of kernel density estimators to a non-degenerate law in L₂(R^d). J. Nonparametr. Statist. 23 129-135.
• Nishiyama, Y. (2009). A uniform law of large numbers for ergodic processes under a Lipschitz condition. Manuscript. [pdf]
• Nishiyama, Y. (2010). Moment convergence of M-estimators. Statist. Neerlandica. 64 505-507. [Proof of Theorem 1]
• 西山陽一・志村隆彰 (2009). 観測ノイズが極値分布に影響を与えないための十分条件. 統計数理 57 443-447. [English version: Research Memorandum 1081, Inst. Statist. Math., pdf]
• Nishiyama, Y. (2009). Asymptotic theory of semiparametric Z-estimators for stochastic processes with applications to ergodic diffusions and time series. Ann. Statist. 37 3555-3579. [pdf, journal site]
• Nishiyama, Y. (2008). Two sample test for counting processes with a non-linear covariate. Research Memorandum 1071, Inst. Statist. Math.
• Masuda, H., Negri, I. and Nishiyama, Y. (2011). Goodness-of-fit test for ergodic diffusions by discrete-time observations: an innovation martingale approach. J. Nonparametr. Statist. 23 237-254.
• Nishiyama, Y. (2008). Donsker's theorem for discretized data. J. Japan Statist. Soc. 38 505-515.
• 西山陽一 (2009). 拡散過程のノンパラメトリック適合度検定. 統計数理 57 83-95.
• Negri, I. and Nishiyama, Y. (2011). Goodness of fit test for small diffusions by discrete time observations. Ann. Inst. Statist. Math. 63 211-225.
• Nishiyama, Y. (2010). Nonparametric inference in multiplicative intensity model by discrete time observation. Ann. Inst. Statist. Math. 62 823-833.
• Negri, I. and Nishiyama, Y. (2009). Goodness of fit test for ergodic diffusion processes. Ann. Inst. Statist. Math. 61 919-928.

Books

• 西山陽一 (2011). マルチンゲール理論による統計解析. 近代科学社. 東京. （xiv + 168 ページ.)　[まえがきと目次]　[正誤表]
• Nishiyama, Y. (2000). Entropy Methods for Martingales. CWI Tract 128, Centrum voor Wiskunde en Informatica, Amsterdam. (viii + 140 pp) [pdf (free)]
  

Some of Unpublished Papers

• Nishiyama, Y. (2011). Proof of Theorem 1 in ``Moment convergence of M-estimators". Manuscript. [pdf]
• Nishiyama, Y. (2009). Parametric estimation for volatility of ergodic diffusion process with unspecified drift. A revised version of Research Memorandum 1093, Inst. Statist. Math. [pdf]
• Nishiyama, Y. (2009). Two sample test for diffusion processes with a non-linear covariate. Research Memorandum 1090, Inst. Statist. Math. [pdf]
• Nishiyama, Y. (2009). A note on semiparametric estimation for ergodic diffusion processes. A revised version of Research Memorandum 1089, Inst. Statist. Math. [pdf]
• Nishiyama, Y. (2009). A uniform law of large numbers for ergodic processes under a Lipschitz condition. Manuscript. [pdf]
• 西山陽一 (2007, revised 2011). マルチンゲール理論の基礎. （解説記事, 20 ページ）[pdf]
• Nishiyama, Y. (1997). Weak convergence of local random fields of kernel density estimators. Preprint 1042, Dept. of Mathemtatics, Utrecht Univ. [pdf]
• Nishiyama, Y. (1996). A central limit theorem for l^∞-valued martingale difference arrays and its application. Preprint 971, Dept.of Mathematics, Utrecht Univ. [pdf]

Full List of Publications