セミナーの案内
講演会のお知らせ
日時：２００９年１月３０日（金）
15:15 - 17:00
講演題目：
1. 15:15 - 16:00
Statistical Analysis of Self-Exciting Point Processes with
Applications to Marketing
2. 16:15 - 17:00
On Kaplan-Meier Integrals
講演者 : Professor
Winfried Stute, Univ. Giessen, Germany
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Abstract of Talk (1):
We propose and study minimum distance estimation (MDE) of para-
meters in the context of point processes. These processes are self-
exciting and have a very general class of compensators. Some non-
parametric inputs drive the associated intensities. An application to
the purchasing behavior and the impact of TV-promotion is studied in
detail.
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Abstract of Talk (2):
The Kaplan-Meier estimator is the efficient nonparametric estimator
of a distribution function, when the data are censored from the right.
Kaplan-Meier integrals are extensions of empirical integrals in that in-
tegration is not taken w.r.t. the classical empirical distribution
function
but to KM. In the first part of this talk I will review my work on KM
over the last 15 years. In the second part some recent extensions to
multivariate censored observations are discussed.
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講演会のお知らせ
日時：２００８年１０月３１日（金）１３：３０−１７：００
場所：早稲田大学国際会議場(総合学術情報センター）、 共同研究室（７）４階
http://www.waseda.jp/jp/campus/index.html
講演題目：
（１）13:30 - 15:00
Inferential aspects of flexible models generated by perturbation of
symmetric distributions.
Professor Anna Clara Monti, University of Sannio, Italy.
(2) 15:30 - 17:00
FROM DISTRIBUTION-FREENESS TO SEMIPARAMETRIC EFFICIENCY
Sixty years of rank-based inference
Professor Marc Hallin, Universite Libre de Bruxelles,
Belgium.
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Abstract of Talk (1):
Flexible models generated by perturbation of symmetric
distributions are
very appealing and suitable for a wide variety of statistical
applications
in a number of different fields because of their nice distributional
properties and various stochastic representations. However, inference
about
these models can be problematic for the following reasons: (i) when the
perturbed symmetric distribution is normal, the information matrix can
be
singular; (ii) the maximum likelihood estimates of the model parameters
that
accommodate skewness and kurtosis can be infinite, even though the true
values of the parameters are finite, and (iii) important sub-models,
such as
the normal distribution, can correspond to values of the model parameter
that are on the boundary of the parameter space.
This talk begins with an overview of flexible models and the problems
for
inference are discussed. Attention then focuses on one popular flexible
model that has recently emerged, the skew-t model. The standardized
indexes
of skewness and kurtosis are both unbounded in this model, so it offers
considerable flexibility for fitting data in which substantial
deviations
from normality occur. Consequently, the skew-t model offers an
alternative
to robust procedures based on y-functions. Model reparametrizations are
available that remedy the problems associated with the singularity of
the
information matrix and inference on the boundary of the parameter space.
These reparametrizations and robustness issues are addressed in the
talk.
--------------------------------
Abstract of TALK (2):
The modern history of ranks in statistics started in 1945 with Frank
Wilcoxon's pathbreaking three pages on rank tests for location.
Emphasis in
1945 was on distribution-freeness and ease of application. Since then,
under
the impulse of such names as Chernoff, Savage, Hodges, Lehmann, Hajek,
and
Le Cam, rank-based methods have followed the development of contemporary
statistics, and turned into a complete body of modern, flexible and
powerful
techniques. In this talk, we show how this evolution, from
distribution-freeness to group invariance and tangent space projections,
eventually may reconcile the enemy brothers of statistics---efficiency
and
robustness.
----------------------------------------
Waseda Seminar on Time Series and Statistical
Finance
基盤研究 (A) 統計科学における数理的手法の理論と応用
( 研究代表者：谷口 正信 (早稲田大学) ) による
日時: 2008年1月22日 (火) 14：00 - 17:00
場所： 早稲田大学理工学部５１号館１８階０６室
MAP： http://www.sci.waseda.ac.jp/campus-map/
講演内容：
（１） 14：00−15：30 ：
Dual P-Values, Evidential Tension and Balanced Tests
Donald Poskitt（ Monash University,
Australia）
（２）
15:30−17:00 ：
On the Theory of Statistical Prediction
Denis Bosq ( Universite Pierre et Marie Curie ( Paris VI )）
Waseda Seminar on Time Series and Statistical
Finance
基盤研究 (A) 統計科学における数理的手法の理論と応用
( 研究代表者：谷口 正信 (早稲田大学) ) による
日時: 2007年12月4日 (火) 14：30より
場所： 早稲田大学理工学部５１号館１８階０６室
MAP： http://www.sci.waseda.ac.jp/campus-map/
講演内容：
（１） 14：30−15：00 ：
Resampling Procedure in Estimation of Optimal Portfolios for
VAR(p) Returns of Assets
白石 博（早稲田大学基幹理工学部）
Abstract
We discuss a resampling proceduer in estimation of optimal
portfolios when the return is a vector-valued non-Gaussian
autoregressive process of order p. Then it is shown a consistency
between the portfolio estimation error and resampled one for the
expected portfolio return and portfolio risk. We construct their
confidence intervals numerically. The result shows that the confidence
intervals are applicable to investigation of actual portfolio
estimation errors.
（２）
15：00−16：30 ：
On goodness of fit tests for diffusion and point processes
Yuri Kutoyants (Universite du Maine, France)
Abstract
We present a review of several results concerning the
construction of the Cramer-von Mises and Kolmogorov-Smirnov type
goodness-of-fit tests for continuous time processes. As the models we
take a stochastic differential equation with small noise, ergodic
diffusion process, Poisson process and self-exciting point processes.
For every model we propose the tests which provide the asymptotic size
$\alpha$ and discuss the behaviour of the power function under local
alternatives. The results of numerical simulations of the tests are
presented.
早稲田統計学研究集会
日時：２００７年１０月５日（金） １５：００−
場所：早稲田大学理工学部５５号館第３会議室
(map) http://www.sci.waseda.ac.jp/campus-map/
講演内容：
（１） １５：００−１５：３０
Empirical likelihood approach for non-Gaussian locally stationary
processes
小方 浩明（早稲田大学国際教養学部）
Abstract
We apply empirical likelihood method to non-Gaussian locally stationary
processes. Based on the central imit theorem for locally stationary
processes, we calculate the asymptotic distribution of empirical
likelihood ratio statistics. Using this method, we can constract
confidence inference on various important indices in time series
analysis.
（２） １５：３０−１６：３０
CONDITIONAL INFERENCE IN THE COINTEGRATED VECTOR AUTOREGRESSIVE MODEL
Kees Jan van Garderen (University of Amsterdam)
Abstract
A VAR model with normal disturbances is a Curved Exponential Model.
Cointegration imposes further curvature, which means that in addition
to reasons for conditioning in nonstationary timeseries given by
Johansen (1995), there are further reasons due to the curvature. This
paper investigates the effects of conditioning for inference on the
speed-of-adjustment coefficients. We show that for some realizations
the sample is far less informative than might be expected ex-ante. This
should be taken into account when making inference. Conditioning is
therefore crucial. We show that conditional inference can be carried
out using the observed information instead of the expected information.
（３） １６：３０−１７：００
Garderen 氏を囲んでの談話会
上記は、萌芽研究（１７６５００８１）（研究代表者 谷口 正信）による。
早稲田統計グループ講演会
日時：２００５年２月７日（月） １６：００−１７：００
場所：早稲田大学理工学部５１号館１７階０６室
(map) http://www.sci.waseda.ac.jp/campus-map/
講演題目： On accuracy of approximations for multivariate scale mixtures in
statistical applications.
講演者：Professor Ulyanov, V.V. ( Moscow State University )
早稲田統計グループ講演会
日時：２００５年１月２１日（金） １５：５０−１６：５０
場所：早稲田大学理工学部５５号館１階第一会議室
(map) http://www.sci.waseda.ac.jp/campus-map/
(通常と場所、時間が異なりますのでご注意ください。)
講演題目： Heavy-tailed elliptical families: optimal inference for shape
講演者：Professor M. Hallin and Professor D. Paindaveine ( Universite Libre
de Bruxelles, Belgium )
早稲田統計グループ講演会
日時：２００４年１２月２１日（火） １６：００−１７：００
場所：早稲田大学理工学部５１号館１７階０８室
(map) http://www.sci.waseda.ac.jp/campus-map/
講演題目： Fractional constant elasticity of variance model
講演者：Professor Ngai Hang Chan ( Chenese University of Hong Kong )
早稲田統計セミナー
日時：２００４年１１月５日 １５：００−１６：００
場所：早稲田大学理工学部５１号館１８階０２室
(map) http://www.sci.waseda.ac.jp/campus-map/
講演題目：Analysis of Longitudinal Data with I(2) Signals
講演者：Prof. Bob. Shumway ( University of California, Davis )
科
学研究費 基盤研究（Ｂ）課題番号 15340204
実解析的方法による非線形発展方程式の解の安定性の研究
研究代表者：柴田 良弘（早稲田大学）
Recent Developments in
Nonlinear Time Series Analysis with Applications to Finance
日時：2004年1月 22-23日
場所：早稲田大学(総合学術情報センター)国際会議場、第三会議室(22日)、第一会議室(23日)
地下鉄東西線早稲田駅下車、徒歩１０分、
(マップ) http://www.waseda.ac.jp/koho/guide/nisiw.html
責任者：谷口 正信（早稲田大学）
プログラム
January 22(Room 3)
Session I ( Chair: Rainer Dahlhaus )
9:30 - 10:10 : LAN theorem for non-Gaussian locally
stationary processes and its applications.
Junichi HIRUKAWA ( Waseda University ) and Masanobu TANIGUCHI ( Waseda
University )
10:10 - 10:50 : Application of Bernstein polynomials for density
function estimation.
Yoshihide KAKIZAWA ( Hokkaido University )
11:00 - 11:50 : Optimal signed rank tests for elliptical VARMA
models.
Marc HALLIN ( Universite Libre de Bruxelles )
Session II ( Chair: Kokyo Naga )
13:00 - 13:40 : Discrimination and clustering for fundamental
frequency patterns of
infant and parent data based on time series regression models.
Hiroko KATO ( NTT Communication Science Laboratories )
and Masanobu TANIGUCHI ( Waseda University )
13:40 - 14:30 : Nearest neighbor ARX modeling of spatial time
series with application
to localization and connectivity study of functional MRI data.
Tohru OZAKI ( Institute of Statistical Mathematics )
14:30 - 15:20 : Solving high-dimensional inverse problems by
spatiotemporal Kalman
filtering.
Andreas GALKA ( Institute of Statistical Mathematics )
Session III ( Chair: Benoit Laine )
15:30 - 16:20 : Signal extraction by state space modeling
Genshiro KITAGAWA ( Institute of Statistical Mathematics )
16:20 - 17:10 : Statistical inference for time-varying ARCH
processes.
Rainer DAHLHAUS ( University of Heidelberg )
---------------------------------------------------------------------------------------
January 23(Room 1)
Session IV ( Chair: Oliver Linton )
9:30 - 10:20 : Finite Sample Distributions of the Empirical
Likelihood Estimator and GMM Estimator.
Naoto KUNITOMO ( University of Tokyo )
10:20 - 11:00 : Change-point detection in time series regression
models.
Takayuki SHIOHAMA ( Hitotsubashi University )
11:00 - 11:50 : Partial mixing and Edgeworth expansion for
stochastic process.
Nakahiro YOSHIDA ( University of Tokyo )
Session V ( Chair: Yoshihide Kakizawa )
13:00 - 13:40 : Outlier detection in time series.
Kokyo NAGA ( Komazawa University )
13:40 - 14:30 : On nonparametric and semiparametric testing of
multivariate time
series. Yoshihiro YAJIMA ( University of Tokyo )
Session VI ( Chair: Marc Hallin )
14:40 - 15:20 : Autoregression depth.
Benoit LAINE ( Universite Libre de Bruxelles )
15:20 - 16:10 : An asymptotic test theory of the fractional
cointegration rank.
Yuzo HOSOYA ( Tohoku University )
16:10 - 17:00 : Estimation of semiparametric ARCH(∞) models by
kernel smoothing.
Oliver LINTON ( London School of Economics )
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Satellite Seminar のお知らせ
(Chair: Masanobu Taniguchi)
January 24, 2004 : 16:00 - 17:00 : School of Science &
Engineering, Waseda University
Room 51- 18 - 02( 早稲田大学理工学部５１号館18
階02 室, ＪＲ高田馬場駅戸山口下車徒歩10分
(マップ) http://www.sci.waseda.ac.jp/campus-map/
Nonparametric MLEs and empirical spectral processes for locally
stationary processes.
By Rainer DAHLHAUS ( University of Heidelberg )
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January 27, 2004 : 16:00 - 17:00 : School of Science &
Engineering, Waseda University
Room 51- 18 - 02( 早稲田大学理工学部５１号館18階02 室)
Asymptotic expansions for some semiparametric
program evaluation estimators.
By Oliver LINTON ( London School of Economics )
---------------------------------------------------------------------------------------
January 29, 2004 : 16:00 - 17:00 : School of Science &
Engineering, Waseda University
Room 51- 18 - 02( 早稲田大学理工学部５１号館18階02 室)
From multivariate location to multivariate autoregression
quantities : conditional depth revisited
By Marc HALLIN and Benoit LAINE ( Universite Libre de
Bruxelles )
日時：１２月１１日（木） １３：３０−１４：３０、１５：００−１６：
００
場所：早稲田大学理工学部５１号館１８階０２室
講演題目：スタインのパラドックスと縮小推定の世界
講演者：東京大学経済学部 久保川 達也氏
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