报告题目： Universality of the largest eigenvalue
of sample covariance matrices
报 告 人： Prof.Wang Zhou,National University
of Singapore
时间地点： 2013年10月24日上午10:30 S709
摘 要： In this talk, I will discuss the universality
of the largest eigenvalue of a class of large dimensional real or complex
sample covariance matrices.
报告题目： Functional integration and index
theory
报 告 人： Prof. JeanMichel Bismut,University
ParisSud, France
时间地点： 2013年10月11日下午4:00 S703
摘 要： In the first part of the talk, I will
explain the connections between the heat equation proof of the index theorem
for Dirac operators, and the localization formulas of DuistermaatHeckman.
In particular, I will show how to pass from integration with respect to
the Brownian measure on the loop space of a Riemannian manifold to integration
of differential forms on this loop space. In the above situation, the
geometry of the loop space is associated with its L2Riemannian metric.
In a second part of the talk, I will show how replacing the L2metric
by a H1metric determines a new measure on the loop space, which corresponds
to a geometric Langevin process, whose generator is a hypoelliptic operator
on the total space of the tangent bundle. I will naturally explain how
the above suggests the possibility of deforming the elliptic Dirac operator
to a family of hypoelliptic Dirac operators.
报告题目： Limit problems for the evolutional
models oftwodimensional Young diagrams
报 告 人： Prof. Bin Xie(谢宾) ,Shishu University,
Japan
时间地点： 2013年9月18日上午10:00 S1013
摘 要： In this talk, we will introducesome
limit problems for a dynamics of twodimensional Young diagrams. The dynamics
of twodimensional Young diagrams is naturally associated with the grandcanonical
ensembles determined from two types of statistics called uniform and restricted
uniform statistics.Under some proper scaling, we will discuss the hydrodynamic
limit and the fluctuation problem for both uniform and restricted uniform
statistics of the evolutional Young diagrams. For the fluctuation problemof
our model, the limits are characterized by two linear stochastic partial
differential equations, whose invariant measures are identical to the
fluctuation limits in the static situations. This talk is based on a joint
work with T. Funaki et al.
报告题目： Least squares estimation of threshold
models: a practical twostage procedure(159)
报 告 人： Dr. Dong Li,Hong Kong University of
Science and Technology, HK
时间地点： 2013年9月6日下午4:00 S712
摘 要： Threshold models have attracted too
much attention and been widely used in econometrics, economics and finance
for modeling nonlinear phenomena. Its success is partially due to its
simplicity in terms of both modelfitting and modelinterpretation. A
popular approach to fit a threshold model is the conditional least squares
method. However, as modeling data with threshold type of models the computational
costs become substantial. This paper proposes a novel method, twostage
gridsearch procedure, to quickly search the least squares estimate of
the threshold parameter in threshold models. Compared with the standard
gridsearch procedure used in literature, our new method extremely reduces
computational costs, which only requires leastsquares operations of order
O(\sqrt{n}). Its validity is also verified theoretically. The performance
of our procedure is evaluated via Monte Carlo simulation studies in finite
samples.
报告题目： Stochastic Calculus for GBrownian
Motion on Manifolds(158)
报 告 人： Prof. Z. Qian,University of Oxford
时间地点： 2013年9月6日下午2:30 S712
摘 要： In this talk I outline how to define
Stratonovich's integration for GBrownian motion via the rough path analysis,
and apply the theory in constructing a class of GBrownian motion on manifolds.
We then identify a class of fully nonlinear equations and obtain stochastic
representation (in viscosity sense) for their solutions. This talk is
based on a joint work with Geng Xi and Danyun Yang at the OxfordMan Institute
in Quantitative Finance, Oxford.
报告题目： Poissonian loop ensemble in discrete
space(157)
报 告 人： 常寅山 博士,Université ParisSud (巴黎11大)
时间地点： 2013年7月30日上午9:30 S712
摘 要： As an analogue and a generalization
of the Brownian loops, the Markovian loops are introduced and studied
mainly by Le Jan. Given a Markov semigroup, Le Jan defines a sigma finite
measure on the space of loops when the bridge measure is welldefined.
The Poissonian loop ensemble (or loop soup) is the Poisson random measure
driven by the Markovian loop measure. The loop model has many relations
with other objects in probability, e.g. random interlacement, Gaussian
free field, branching process with immigration, uniform spanning tree,
permenantal fields, etc.
In this talk, we will mainly present the basic properties and interesting
results based on the work of Le Jan, Sznitman, Lemaire, Lupu, … We will
restrict ourselves on Markovian loops on discrete space. To be more precise,
we will talk about the compatibility of the loop soup, the occupation
field, the loop clusters together with a few relations with other fields.
报告题目： Consistent CrossValidation for
Tuning Parameter Selection in HighDimensional Variable Selection(156)
报 告 人： Yang Feng, Assistant Professor Department
of Statistics, Columbia University, USA
时间地点： 2013年7月22日上午10:00 S708
摘 要： Asymptotic behavior of tuning parameter
selection in the standard crossvalidation methods is investigated for
the highdimensional variable selection. It is shown that the shrinkage
problem with LASSO penalty is not always the true reason for the overselection
phenomenon in crossvalidation based tuning parameter selection. After
identifying the potential problems with the standard crossvalidation
methods, we propose a new procedure, Consistent CrossValidation (CCV),
for selecting the optimal tuning parameter. CCV is shown to enjoy the
model selection consistency. Extensive simulations and real data analysis
support the theoretical results and demonstrate that CCV also works well
in terms of prediction.
报告题目： Stochastic variational principles
and FBsde's on Lie groups(155)
报 告 人： Prof. Ane Bela Cruzeiro, Grupo de
Física Matemática da Universidade de Lisboa, Portugal
时间地点： 2013年7月19日下午2:30 S712
摘 要： We prove a EulerPoincaré reduction
theorem for stochastic processes taking values in a Lie group and show
examples of its application, notably to the derivation of NavierStokes
equations. We also show the relations of such processes with forwardbackward
stochastic systems. This is joint work with Marc Arnaudon (Bordeaux) and
Xin Chen (Lisbon).
报告题目： Functional Linear MixedEffects
Model in Characterizing Population Trend and Variability of Circadian
Rhythm using Actigraphy Data(154)
报 告 人： Jimin Ding, Assistant Professor, Washington
University in St. Louis
时间地点： 2013年7月18日下午3:30 S712
摘 要： We propose a functional linear mixedeffects
model to investigate correlated functional curves with application to
the actigraphy data collected from a study of sleep disorders. The study
has been conducted in the Medical School of Washington University in Saint
Louis, which contains actigraphy data over a week for each subject. An
actigraph is a watchlike device attached to the wrist or leg that contains
accelerometers to measure movements minutebyminute throughout the day
of each day it is worn. The resulting data are densely measured activity
levels over 24hour period for several days for each patient. We view
them as curves over time clustered by subjects and model these data using
the functional linear mixedeffects model to incorporates multiple ixedeffects
and randomeffects functions of arbitrary form. The proposed model is:
a generalization of 1) functional linear models by including randomeffects
functions; 2) linear mixedeffects models to the functional space. We
develop a new method to iteratively estimate the population trends and
decompose the functional variation from between and within subject.
The individual profile prediction are adaptively shrunk toward the population
average. We apply the proposed functional linear mixedeffects model to
investigate the relationship between the clinical covariates and activities
of the patients, discover the major variation directions, describe the
circadian rhythm and reveal some interesting insights into patient's activity
patterns.
报告题目： Bayesian analysis in partially
identified models(153)
报 告 人： Yuan Liao, Assistant Professor,Department
of Mathematics, University of Maryland
时间地点： 2013年7月15日下午4:30 S708
摘 要： One of the fundamental questions for
Bayesian analysis is how much prior information can be updated by the
data. In many applications of econometrics and survival analysis, the
available information from the data is not strong enough to identify the
parameter of interest. Instead, the parameter is only ``partially identified"
on a nonsingleton set. While the prior information is often washed away
by the data as sample size diverges in traditional models, it is no longer
the case in partially identified models. Instead, the shape of the posterior
is determined by the prior even asymptotically, and the classical Bernsten
von Mises theorem does not hold. I will discuss many applied examples
to motivate partially identified models, and introduce some recent asymptotic
results on the posterior distributions. I will also construct Bayesian
credible intervals in the new framework, and both the Bayesian and frequentist
coverage probabilities are investigated and compared.
报告题目： The Clark Formula of Generalized
Levy Functionals(152)
报 告 人： Prof. YuhJia Lee （李育嘉），National University
of Kaohsiung, Taiwan
时间地点： 2013年7月15日下午4:00 S709
摘 要：
报告题目： The Asymptotic Expansion of Forward
Equations of Singularly Perturbed Diffusion (151)
报 告 人： Prof. TzuuShuh Chiang (姜祖恕），Institute
of Mathematics Academia Sinica, Taiwan
时间地点： 2013年7月15日下午3:00 S709
摘 要：
报告题目： The Kolmogorov Filter(150)
报 告 人： Prof. Hui Zou, University of Minnesota
时间地点： 2013年7月11日下午4:00 S709
摘 要： Variable screening techniques have
been proposed to mitigate the impact of high dimensionality in classification
problems, including ttest marginal screening (Fan & Fan, 2008) and
maximum marginal likelihood screening (Fan & Song, 2010). However,
these methods rely on strong modelling assumptions that are easily violated
in real applications. To circumvent the parametric modelling assumptions,
we propose a new variable screening technique for binary classification
based on the Kolmogorov–Smirnov statistic.We prove that this socalled
Kolmogorov filter enjoys the sure screening property under much weakened
model assumptions. We supplement our theoretical study by a simulation
study.
报告题目： Imprinting Test of Disease Associated
SNPs under mixture model
报 告 人： 郭建华 教授,东北师范大学数学与统计学院、 应用统计教育部重点实验室
时间地点： 2013年6月27日上午10:00 S709
摘 要： Genomic imprinting represents a known
aspect of the etiology of schizophrenia, a serious and common neuropsychiatric
disease. This study delineates the significance of imprinting on the relationships
between schizophreniaassociated singlenucleotide polymorphisms (SNP)
of the GABRB2 gene for the subunit of receptors and the quantitative trait
of GABRB2 mRNA expression. The imprinting phenomenon depicts differential
expression levels of the allele depending on its parental origin. When
the parental origin is unknown, the expression level has a finite normal
mixture distribution. A random sample on expression levels from a population
is naturally divided into three subsamples according to the number of
minor alleles an individual possesses. This understanding leads to a likelihood
ratio test (LRT) for the presence of the imprinting. Due to nonregularity
of the finite mixture model, the classical asymptotic conclusions on likelihoodbased
inferences are inapplicable. In this paper, we first prove the maximum
likelihood estimator of the mixing distribution is consistent in the current
setting. We find the LRT statistic has an elegant null limiting distribution.
Simulation studies confirm the limiting distribution provides precise
approximations to the finite sample distributions in various parameter
settings. The LRT is applied to expression data sets on the schizophrenia
susceptibility gene GABRB2. Our analyses provide evidences of imprintings
on a number of isoform expressions of its receptor subunit protein encoded
by the GABRB2 gene.
报告题目： 非平稳时间序列的理论及应用
报 告 人： 高集体 教授，Monosh University, Australia
时间地点： 2013年6月21日下午2:00 S703
简 介：
报告题目： 分位数回归模型的若干研究
报 告 人： 朱仲义 教授,复旦大学统计系
时间地点： 2013年6月25日下午4:00 S712
摘 要： 在这个讲座中,我们将首先介绍分位数回归模型的一般特性,其次在三个方面介绍我们最近的研究成果:1.对分位数回归模型，我们提出了一种统一的变量选择方法，此方法能够选择变量，同时能够区分常系数和变系数；2.对自变量带有测量误差的分位数回归模型，我们利用校正得分函数的方法，提出了相合估计方法，并且在理论和数值模拟上证实了方法的有效性；3.
基于CSUM方法，对分位数回归模型我们提出了一种变点的检验和估计方法。通过理论和模拟分析，新方法优于其他方法。
报告题目： Flexible Modeling of Medical Cost
Data
报 告 人： Lei Liu（刘磊）, PhD,Associate Professor,Department
of Preventive Medicine Northwestern University，USA
时间地点： 2013年6月25日下午4:00 S712
摘 要： Medical cost data are often skewed
to the right and heteroscedastic, having a nonlinear relation with covariates.
To tackle these issues, we consider an extension to generalized linear
models by assuming nonlinear covariate effects in the mean function and
allowing the variance to be an unknown but smooth function of the mean.
We make no further assumption on the distributional form. The unknown
functions are described by penalized splines, and the estimation is carried
out using nonparametric quasilikelihood. Simulation studies show the
flexibility and advantages of our approach. We apply the model to the
annual medical costs of heart failure patients in the clinical data repository
(CDR) at the University of Virginia Hospital System. We also discuss how
to adopt this modeling framework in correlated medical costs data.
报告题目： A rotational approach to high dimensional
classification
报 告 人： Ning Hao, Associate Professor,Department
of Mathematics, the University of Arizona, USA
时间地点： 2013年6月13日下午3:30 S712
摘 要： Many high dimensional classification
techniques have been proposed in the literature based on sparse linear
discriminant analysis (LDA). To efficiently use them, sparsity of linear
classifiers is a prerequisite. However, this might not be readily available
in many applications and rotations of data are required to create the
needed sparsity. In this talk, we propose a surprisingly simple rotation
to create the required sparsity. The proposed rotateandsolve procedure
can be combined with any existing classifiers, and is robust against the
sparse level of the true model. We show that this rotation does create
the sparsity needed for high dimensional classifications. The methodological
power is demonstrated by a number of simulation and real data examples
and the improvements of our method over some popular high dimensional
classification rules are clearly shown.
报告题目： Machine Learning and Its Application
in Variable Annuity Hedging
报 告 人： Guojun Gan博士，Director, VA Hedging
Research & Development Manulife Financial, Toronto, Ontario, Canada
时间地点： 2013年6月13日上午10:00 S709
简 介：
报告题目： A generalization of Fourier series
expansion and its involvements in mathematics
报 告 人： Prof.Tao QIAN,University of Macau
时间地点： 2013年4月27日下午4:00 S1013
简 介： Rational orthogonal expansions can
be considered as generalizations of Fourier series expansion. We introduce
the so called Adaptive Fourier Decomposition (AFD) and its relations to
a number of mathematical subjects, including best nrational approximation,
BeurlingLax backward shift operator invariant subspaces, phase and amplitude
retrieval problems, etc.
报告题目： Scalable Spectral Algorithms for
Community Detection in Directed Networks
报 告 人： Tao Shi, Associate Professor,Department
of Statistics, Department of Computer Science and Engineering，The Ohio
State University
时间地点： 2013年4月17日下午2:00 S712
简 介： Community detection has been one of
the central problems in network studies and directed network is particular
challenging due to asymmetry among its links. In this talk, we discuss
incorporating the direction of links reveals new perspective on communities
regarding to two different roles, source and terminal. Intriguingly, such
communities appear to be connected with unique spectral property of the
graph Laplacian of the adjacency matrix and we exploit this connection
by using regularized SVD methods. We propose harvesting algorithms, coupled
with regularized SVDs, that are linearly scalable for efficient identification
of communities in huge directed networks. The algorithm showed great performance
and scalability on benchmark networks in simulations and successfully
recovered communities in real social networks applications (with ~2 million
nodes and ~50 million edges). This is a joint work with Sungmin Kim (OSU).
报告题目： 统计质量控制图简介及某些热点研究问题
报 告 人： 王兆军 教授,南开大学
时间地点： 2013年3月15日下午4:00 S712
简 介： 主要介绍统计质量控制图的一些基本概念和近十年的三个热点研究问题：关于profilde，healthcare数据的监控以及高维复杂数据的在线监控。
报告题目： Semiparametric Models for Longitudinal
Count Responses with Overdispersion and Structural Zeros
报 告 人： Wan Tang,Associate Professor , University
of Rochester Dept of Biostatistics and Computational Biology
时间地点： 2013年3月11日上午10:00 S709
简 介： Overdispersion and structural zeros
are two major manifestations of departure from the Poisson assumption
when modeling count responses using Poisson loglinear regression. Ignoring
such departures could yield bias and lead to wrong conclusions. Different
approaches have been developed to tackle these two major problems. In
this talk, we review available methods for dealing with overdispersion
and structural zeros within a longitudinal data setting and propose a
new semiparametric modeling approach to address the limitations of these
methods. We illustrate our approach with both simulated and real study
data.
报告题目： Semiparametric Estimation in Linear
Dynamic Panel Data Models
报 告 人： Prof.Liqun Wang, Department of Statistics,
University of Manitoba, Canada
时间地点： 2013年3月8日下午4:00 S712
简 介： Repeated measures data are common in
many research areas. In statistics, the mainstream research adopts nonlinear
mixedeffects models to describe the response variables through some other
covariates. In contrast, in econometrics dynamic models are mainly used
to predict the response through its own past values. It is interesting
to see the connections and differences between these two approaches. We
study the secondorder least squares estimator for the autoregressive
panel data models. This method requires only the specification of the
first two conditional moments of the unobserved effects given the process
initial observation, and does not require any other distributional assumptions.
The data generating process can be either stationary or nonstationary.
The proposed estimator is consistent and asymptotically normal for large
N and finite T under fairly general regularity conditions. Moreover, we
show that our estimator reaches an optimal semiparametric efficiency bound.
Monte Carlo simulation studies show that the proposed estimator performs
satisfactorily in finite sample situations compared to the usual firstdifferenced
generalized method of moment (GMM) and the random effects pseudo maximum
likelihood (PML) estimators.
报告题目： Semiparametric Estimation in Linear
Dynamic Panel Data Models
报 告 人： Prof.Liqun Wang,Department of Statistics,
University of Manitoba, Canada
时间地点： 2013年3月5日下午4:00 S712
简 介： Repeated measures data are common in
many research areas. In statistics, the mainstream research adopts nonlinear
mixedeffects models to describe the response variables through some other
covariates. In contrast, in econometrics dynamic models are mainly used
to predict the response through its own past values. It is interesting
to see the connections and differences between these two approaches.We
study the secondorder least squares estimator for the autoregressive
panel data models. This method requires only the specification of the
first two conditional moments of the unobserved effects given the process
initial observation, and does not require any other distributional assumptions.
The data generating process can be either stationary or nonstationary.
The proposed estimator is consistent and asymptotically normal for large
N and finite T under fairly general regularity conditions. Moreover, we
show that our estimator reaches an optimal semiparametric efficiency bound.
Monte Carlo simulation studies show that the proposed estimator performs
satisfactorily in finite sample situations compared to the usual firstdifferenced
generalized method of moment (GMM) and the random effects pseudo maximum
likelihood (PML) estimators.
报告题目： Large deviation principles for
generalized FeynmanKac functionals and $L^p$independence of spectral
radius
报 告 人： Prof. Kuzuhiro Kuwae, Kumamoto University
时间地点： 2013年2月20日下午4:00 S703
简 介： I will talk about the large deviation
principles of occupation distribution for generalized FeynmanKac functionals
are presented in the framework of symmetric Markov processes having doubly
Feller or strong Feller property under mild conditions on measures. As
a consequence, we expose the $L^p$independence of spectral radius of
our generalized FeynmanKac functionals. The result extends the works
on LDPs by Takeda, TakedaTawara and Tawara. This is a joint work with
D. Kim and Y. Tawara, which is a continuation of the previous joint work
with De Leva and Kim published in JFA. If I have a time, we mention the
Fukushima's decomposition in the strict sense for functions locally in
the domain of Dirichlet form having energy measure of Dynkin class without
assuming no inside killing.
报告题目： A generalized beta copula with
applications in modeling multivariate longtailed data
报 告 人： Prof. Zhengjun Zhang,University of
Wisconsin，USA
时间地点： 2013年1月9日下午2:00 S703
简 介： This work proposes a new copula class
that we call the MGB2 copula. The new copula originates from extracting
the dependence function of the multivariate GB2 distribution (MGB2) whose
marginals follow the univariate generalized beta distribution of the second
kind (GB2). The MGB2 copula can capture nonelliptical and asymmetric
dependencies among marginal coordinates and provides a simple formulation
for multidimensional applications. The new class features positive tail
dependence in the upper tail and tail independence in the lower tail.
Furthermore, it includes some wellknown copula classes, such as the Gaussian
copula, as special or limiting cases. The validation of the MGB2 copula
can be assessed by a graphical tool of the socalled “conditional plots”.
To illustrate the usefulness of the MGB2 copula in practice, we build
a trivariate model to analyze a data set that contains rich information
on bodily injury liability claims closed within twoweek period in years
1987, 1992, and 1997. Reparametrized logF (EGB2) distributions are chosen
to accommodate the rightskewness and the longtailedness of the outcome
variables,while continuous predictors are fitted by nonlinear curves
in the marginal regression models. The pairwise dependence structures
exhibited motivate the application of the MGB2 copula. For comparison
purposes we also consider the alternative Gumbel copula and t copula for
the adaption of the upper tail dependence. The quantitative and graphical
assessment for goodnessoffit demonstrates the comparative advantage
of the MGB2 copula over the other two copulas, which practically establishes
the necessity for the development of this new copula class.
