**Fridays 1-2 pm, Rm Mth 2400
Spring '09**

**Eric
Slud
Statistics Program ,
Math Department
Rm 2314 x5-5469**

Interested participants should send email to
**evs@math.umd.edu**

**Research Focus:** Semiparametric statistical theory, which is
broadly speaking about the estimation of

finite-dimensional
(`structural') parameters like regression coefficients in the presence
of infinite-

dimensional `nuisance ' parameters like unknown error
distributions in regression or like unknown

baseline hazard functions
and censoring distributions in survival regression problems.

Much of the research in this field has been done in a biostatistical setting;
econometricians have also

worked heavily in it. We will cover some of
the basic examples (Cox model, `accelerated failure

models' as an
instance of right-censored regression models), which I hope will be
presented by RIT

participants after a couple of introductory
lectures. After that we will proceed according to the interests

of
participants, but with at least some attention to "biased sampling"
semiparametric models which

relate to survey weights.

** For those that are new to the
Semiparametrics topic, the essential introductory reading is Chapter
25 of the van der Vaart book, Sections 25.1-25.5. That is what the
introductory talks are based on. From there, the Examples will be
expanded using journal papers and (for some topics) the Tsiatis
book.**

**Graduate-student Prerequisites:** To benefit from this research
activity, a graduate student

should have completed Stat 700-701
and Stat 600-601.

**Graduate Program:** Graduate students will be involved in
reading and presenting

papers from the statistical literature
concerning provable properties of semiparametric estimators.

**Work Schedule:** We will meet weekly in the spring of 2009.
Students will choose

from the following list of Topics and Papers
(which will regularly be augmented on

this web-page) and present
the material in subsequent weeks, after an introductory

couple of
weeks' talks by me. Presentations can be informal, but should be
detailed

enough and present enough background that we can
understand the issues and ideas

clearly. It is expected that
many presentations will extend to a second week.

**Topics by Keyword:
**

or by a biased sampling design,

spline density estimation techniques.

(i) Bickel, P., Klaassen, C., Ritov, Y. Wellner, J. (1993),
*Efficient and Adaptive Estimation for Semiparametric Models,*
Johns Hopkins Univ. Press: Baltimore.

This is now re-issued as a Springer paperback, but is very difficult to read.

(ii) LeCam, L. & Yang, G. (1990), *Asymptotics in Statistics: Some
Basic Concepts*, Springer-Verlag: New York.

A good and readable text on contiguity theory, local asymptotic
normality and applications.

(iii) Van der Vaart, A. (1998, paperback edition 2000) *Asymptotic
Statistics*, Cambridge Univ. Press.

This text was used in Stat 710 a couple of years ago and will be used
now in introducing the semiparametrics

topic. It contains excellent
introductory chapters on contiguity and empirical processes and
semiparametrics.

(iv) Tsiatis, A. (2006) *Semiparametric Theory and Missing Data*
(Springer Series in Statistics).

(v) Hastie, T. J. and Tibshirani, R. J. (1990). *Generalized
Additive Models.* Chapman & Hall/CRC.

Chen, Jinbo and Norman Breslow (2004) * Semiparametric efficient
estimation for the auxiliary outcome
problem with the conditional mean model* Canad.
Jour. Statist.

Gilbert, Peter B. (2000) *Large sample theory of maximum
likelihood estimates in semiparametric
biased sampling models*.
Ann. Statist.

Godambe, V.P. and Heyde, C. 1987 ISI review paper on
*Quasi-likelihood and optimal estimation*.

Kosorok, M., Lee, B., and Fine, J. (2004) *Robust inference for
proportional hazards univariate frailty
regression
models*. Ann. Statist.

Lai, T.L. and Ying, Z. (1992) *Asymptotically efficient
estimation in censored and truncated
regression models*. Statistica
Sinica

Li, Haihong, Lindsay, Bruce G. and Waterman, Richard P. (2003)
*Efficiency of projected
score methods in
rectangular array
asymptotics. *J. Roy. Statist. Soc. Ser. B

Lindsay, Bruce, Clogg, C., and Grego, J. (1991)
*Semiparametric estimation in the Rasch
model and related
exponential response models, including a simple latent class
model for item
analysis. *J. Amer. Statist. Assoc.

Parner, E. (1998) *Asymptotic theory for the correlated
gamma-frailty model*. Ann. Statist. **26**, 183-214.

Pfeffermann, D. and Sverchkov, M. * work on survey data with
semiparametrically modelled
informative
nonresponse*

Qin, J. (1994?) Ann. Statist. papers on empirical likelihood

Rotnitzky and Robins papers (some with other co-authors) on
inverse-probability weighted estimating equations for

longitudinal
studies (eg AIDS) with informative dropout patterns

Slud, E. and Vonta, I. (2005) *Efficient semiparametric
estimators via modified profile likelihood*. Jour. Statist.

Planning & Inference **129**, 339-367.

**Organizational meeting:**January 30. Eric Slud will give brief introductory talk and outline some topics of interest.**Approaches to finding semiparametric efficient estimators:**Feb. 6, Eric Slud

This talk contained more preliminary material from the van der Vaart book, together with some general comments

about approaches in the literature to finding, semiparametric efficient estimators. For a pdf file of slides summarizing

the talks on Jan. 30, Feb. 6, and Feb. 20, see Semiparametric Efficiency Slides.**Semiparametic estimators in purely nonparametric or symmetric location problems:**February 13, Paul Smith.

**Loose ends related to characterizing optimality of efficient influence functions and semiparametric estimators,**February 20, Eric Slud & Paul Smith.

with more examples:

**Missing data problems**from Tsiatis book: Feb. 27, Neung Soo Ha

**Additional discussion about semiparametric efficiency and operator inversion**, from

Semiparametric Efficiency Slides linked above and conference talk about Slud-Vonta paper: March 6, Eric Slud

**Semiparametric Efficiency in Cox Model**from Bickel et al. book and some papers: March 13, Jiraphan Suntornchost

**Partially linear models**from Hastie and Tibshirani papers and books: March 27, David Shaw

**Estimating equations methods related to missing data**as in Chen & Breslow paper listed above: April 3, Ziliang Li

Ziliang continued to speak April 10, and April 17.

- No talk is scheduled April 24, and this meeting will be cancelled.

**A semiparametric hazard model in Econometrics**will be the topic for our final talk, by Huitian (Emmy) Lei May 1.

**No RIT Meeting on May 8.**

Last updated April 17, 2009.