Washington Statistical Society

Washington Statistical Society Seminars

Current | 2009 | 2008 | 2007 | 2006 | 2005 | 2004 | 2003 | 2002 | 2001 | 2000 | 1999 | 1998 | 1997 | 1996 | 1995 | Methodology

Download Area Meetings and Courses (pdf)

November 2009
5	Thur.	(Bio) Statistics Seminar Series Office of Biostatistics Research Division of Prevention and Population Sciences Pattern Analysis of Pairwise Relationship in Genetic Network
5	Thur.	University of Maryland Statistics Seminar A Class of Multivariate Distributions Related to Distributions with a Gaussian Component
10	Tues.	Panel on Address-Based Sampling
10	Tues.	ASA Survey Research Methods Section Webinar Dual Frame Theory Applied to Landline and Cell Phone Surveys
13	Fri.	Computer-Intensive Statistical Methodology with Applications to Translational Cancer Research
13	Fri.	George Washington University The Institute for Integrating Statistics in Decision Sciences What Data Mining Teaches Me About Teaching Statistics
16	Mon.	George Washington University Department of Statistics Combined State and Parameter Estimation in General State-Space Models
19	Thur.	Empirical Likelihood Based iInference for Quantilesand Low Income Proportions in Selection Bias and Missing Data Problems
19	Thur.	George Washington University Department of Statistics Moment Determinancy of Distributions: Some Recent Results
December 2009
2	Wed.	Data, Information and Interpretation in Assessing the Sustainability of the Nation's Forests
16	Wed.	Geographic Information (GIS) Data Collection and Storage
17	Thur.	Comparing the Census Bureau's Master Address File (MAF) with both Fresh Area Listing and Commercial Address Lists

Notice about Seminars at the Bureau of Labor Statistics

To be placed on the seminar attendance list at the Bureau of Labor Statistics (BLS), you need to email your name, affiliation and seminar name to wss_seminar@bls.gov (note that there is an underscore after wss') by noon at least two days in advance of the seminar or call 202-691-7524 and leave a message with this information.

BLS is located at 2 Massachusetts Avenue, NE. Washington, DC. The Visitor's Entrance is on 1st Street and is opposite Union Station. Remember to bring a photo ID.

(BIO)STATISTICS SEMINAR SERIES
OFFICE OF BIOSTATISTICS RESEARCH
DIVISION OF PREVENTION AND POPULATION SCIENCES

Title: Pattern Analysis of Pairwise Relationship in Genetic Network

In recent times genetic network analysis has been found to be useful in the study of gene-gene interactions, and the study of gene-gene correlations is a special analysis of the network. There are many methods for this goal. Most of the existing methods model the relationship between each gene and the set of genes under study. These methods work well in applications, but there are often limitations on network size, issues of non-uniqueness of solution and/or computational difficulties, and interpretation of results. Here we study this problem from a different point of view: given a measure of pairwise gene-gene relationship, we use the technique of pattern image restoration to infer the optimal network pairwise relationships. In this method, the genetic network can be of any size, the solution always exists and is unique, and the results are easy to interpret in the global sense and is computationally simple. The regulatory relationships among the genes are inferred according to the principle that neighboring genes tend to share some common features. The network is updated iteratively until convergence, each iteration monotonously reduces entropy and variance of the network, so the limit network represents the clearest picture of the regulatory relationships among the genes provided by the data and recoverable by the model. The method is illustrated with a simulated data and applied to real data sets. This is a joint work with George Bonney.

UNIVERSITY OF MARYLAND
STATISTICS SEMINAR

Title: A Class of Multivariate Distributions Related to Distributions with a Gaussian Component

A class of random vectors (X, Y), X 2 Rj , Y 2 Rk with characteristic functions of the form

where C is a (jxk)-matrix and prime stands for transposition is introduced and studied. The class possesses some nice properties that will be discussed. A relation of the class to random vectors with Gaussian components is of a particular interest. The goal was to understand what kind of restrictions on the marginal distributions are imposed by an attempt to preserve Gaussianlike properties.

Title: Panel on Address-Based Sampling

Each panelist will give a brief (10-15 minutes) discussion of their experiences in implementing address-based sample designs. Possible topics include, but are not limited to: coverage issues, cost, data quality, survey management, and questionnaire design. Ample time will be allotted for questions following the panelists' remarks.

Title: Computer-Intensive Statistical Methodology with Applications to Translational Cancer Research

Early detection is critical in disease control and prevention. Biomarkers provide valuable information about the status of a cell at any given time point. Biomarker research has benefited from recent advances in technologies such as gene expression microarrays, and more recently, proteomics. The long term translational research goal is that if drugs can be targeted to specific tissues in the body, then dosage can be altered to achieve the desired effect while minimizing side effects such as toxicity. Motivated by specific problems involving such high throughput data, I have developed computer-intensive statistical methods based on nonparametric and semiparametric mixture model assumptions for real-time analysis in the context of biomarker discovery. Most biomarker-discovery projects aim at identifying features in the biomarker profiles (gene expression, phage, SAGE, mass spectrometry proteins) that distinguish cancers from normals, between different stages of disease development, or between experimental conditions (such as different treatment arms or different tissue types). Novel statistical methodology development will be highlighted with direct applications to cancer research challenges that address our long term translational goal.

GEORGE WASHINGTON UNIVERSITY
THE INSTITUTE FOR INTEGRATING STATISTICS IN DECISION SCIENCES

Title: Moment Determinancy of Distributions: Some Recent Results

The main discussion will be on distributions and their properties expressed in terms of the moments which are assumed to be finite. We describe distributions which are unique (M-determinate) and others which are non-unique (M-indeterminate). We also show the practical importance of these properties in areas such as Financial modelling and Reliability analysis.

We start briefly with classical criteria and turn to very recent developments based on the so-called Krein-Lin techniques. Thus we will be able to analyze Box-Cox functional transformations of random data and characterize the moment determinacy of their distributions. Distributions of stochastic processes such as the Geometric BM and the solutions of SDEs will also be considered.

All statements and criteria will be well illustrated by examples involving popular distributions such as Normal, Skew-Normal, Log-normal, Skew-Log-Normal, Exponential, Gamma, Poisson, IG, etc. Several facts will be reported, it seems some of them are not so well-known, they are a little surprising and even shocking.

The material will be addressed to professionals in Statistics/Probability, Stochastic modeling and also to Doctoral and Master students in these areas. If time permits, some open questions will be outlined.

GEORGE WASHINGTON UNIVERSITY
DEPARTMENT OF STATISTICS

Title: Combined State and Parameter Estimation in General State-Space Models

his talk considers the problem of combined state and parameter estimation in general state-space models. Working within the Bayesian framework, we derive simulation-based (MCMC and sequential Monte Carlo) strategies for filtering, smoothing and parameter estimation. The approaches are quite general and can be applied to a wide class of models, including nonlinear, non-Gaussian and continuous-time models. We illustrate the methods using a stochastic volatility jump-diffusion model and a dynamic spatio-temporal model.

Title: Empirical likelihood based inference for quantiles and low income proportions in selection bias and missing data problems

In this talk, we study covariate-adjusted median treatment effects based on the empirical likelihood method. This method is useful for studying treatment effects on skewed variables in studies where treatment is not randomly assigned. A closely related problem is to estimate the low income proportion on a sample subject to nonresponse that is ignorable given measured covariates but is not completely random. The low income proportion is defined as the proportion of the population income falling below a given fraction A(0<A<1) of the Bth (0<B< 1) quantile of the income distribution. It is an important index in comparisons of poverty in countries around the world. The stability of a society depends on this index heavily. An accurate and reliable estimation of this index plays an important role for government's economic policies.

GEORGE WASHINGTON UNIVERSITY
DEPARTMENT OF STATISTICS

Title: What Data Mining Teaches Me About Teaching Statistic

Data mining has been defined as a process that uses a variety of data analysis and modeling techniques to discover patterns and relationships in data that may be used to make accurate predictions and decisions. Statistical inference concerns the same problems. Are the two really different? Through a series of case studies, we will try to illuminate some of the challenges and characteristics of data mining. Each case study reminds us that the important issues are often the ones that transcend the methodological choice one faces when solving real world problems. What lessons can these teach us about teaching the introductory course?

Title: Data, Information and Interpretation in Assessing the Sustainability of the Nation's Forests

The Montreal Process Criteria and Indicators for Forest Sustainability (MP C&I) provide the foundation for the 2010 National Report on Sustainable Forests, a major Forest Service reporting effort currently underway. The processes through which the MP C&I were derived and applied as well as the specific content of selected indicators will be the focus of this talk. The MP C&I include 64 indicators spanning ecological, economic and social dimensions associated with the sustainability of forest ecosystems, and they entail a host of technical and conceptual issues related to data gathering, reporting and interpretation. Moreover, the underlying concept of sustainability presents various challenges both when considered generally and within the context of specific indicators. These topics and others will be discussed within the general context of presenting the overall findings of the 2010 Report.

Title: Geographic Information (GIS) Data Collection and Storage

This presentation will describe methods creating geographic data, storing it in a database, and displaying it for analysis. We will detail methods of data collection, what attributes differentiate GIS data from other types of data, and how to best format the data for storage in a database.

Once the data are geographically referenced in a database, we will further explore how these GIS data can be accessed and displayed with data from other sources to further enhance its usability. These other sources of data can be internal or external to your organization. We will discuss some of these external data sites as well as detail how they disseminate their GIS data.

Title: Comparing the Census Bureau's Master Address File (MAF) with both Fresh Area Listing and Commercial Address Lists

This is an expanded version of two talks from the JSM. In the first talk, Loudermilk reports on joint work with Mei Li to assess the suitability of the MAF as a replacement for the frame for current surveys at the Census Bureau such as the Current Population Survey. They used fresh area listings for this purpose. In the second talk, Kennel reports on joint work with Mei Li to compare the coverage of a commercially available address list with that of the MAF and to that from the same fresh area listings produced to study MAF coverage. Together, these talks should be of high interest to sampling statisticians both inside and outside of the federal government.