1996 Hartley Lectures

Department of Statistics
Texas A&M University

The Texas A&M University Department of Statistics

presents the

H.O. HARTLEY MEMORIAL LECTURES

October 14, 16 and 17, 1996

Lecturer: WAYNE A. FULLER
Distinguished Professor in Liberal Arts and Sciences, Iowa State University

The H. O. Hartley Memorial Lectures were established by the Texas A&M University Department of Statistics in 1988 to honor the memory of Herman Otto Hartley. Hartley accepted an appointment as Distinguished Professor at Texas A&M in 1963, founded Texas A&M's Institute of Statistics, and served as its director until his retirement in 1977. Hartley built his initial faculty of four into a group of 16, directed more than 30 doctoral students, and published over 75 papers during this period. He served as president of the American Statistical Association in 1979. Professor Hartley died on December 30, 1980.

Hartley was well known for his work on the foundations of sampling theory, and also made important contributions to mathematical optimization, estimation with incomplete data, estimation of variance components, and establishment of safe doses in carcinogenic experiments. Hartley collaborated with Egon Pearson to produce the classic two-volume Biometrika Tables for Statisticians.

Hartley earned a Ph.D. degree in mathematics at Berlin University in 1934, and a Ph.D. degree in statistics under John Wishart at Cambridge University in 1940. He taught at University College, London and Iowa State College before coming to Texas A&M. Hartley was deeply committed to all phases of his profession, including education, research, and delivery of knowledge and advice to users of statistics. H. O. Hartley was not only brilliant academician, but also a warm and caring human being. His legacy continues to have a profound influence on Texas A&M students and the larger statistical community.

The H. O. Hartley Memorial Lectures are held every other year, and were first given in 1988 by Peter J. Diggle. Subsequent lecturers have been Bradley Efron, E. J. Hannan and Sir David R. Cox. This year the Department of Statistics is honored to have Professor Wayne A. Fuller present the Hartley Lectures. Dr. Fuller is a Distinguished Professor in Liberal Arts and Sciences at Iowa State University. His many honors include elected membership in the International Statistical Institute, being elected a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the Econometric Society, and election as Vice President of the American Statistical Association in 1990. He is renowned worldwide as an expert in several fundamentally important areas of statistics, including time series, measurement error models, survey sampling and econometric statistics.

Professor Fuller has written two important and influential books, Introduction to Statistical Time Series and Measurement Error Models, both of which were published by John Wiley & Sons. Over the course of his career he has been the author or co-author of more than 100 refereed publications, has directed the research of 55 Ph.D. students and 26 Master of Science students, and has been principal investigator or a participant on research grants from the National Resources Conservation Service, the National Agricultural Statistics Service, the Census Bureau and the Bureau of Labor Statistics.

Professor Fuller's breadth of knowledge is well-evidenced by the diversity of the three topics he has chosen for this year's Hartley lectures, abstracts of which are given below.

ADJUSTMENTS FOR NONRESPONSE IN LONGITUDINAL SURVEYS
4:00 p.m. Monday, October 14, 1996
Lecture Room A, Clayton W. Williams, Jr. Alumni Center

Regression estimation for survey samples is reviewed. Conditions under which the regression estimator is consistent for the population mean in the presence of nonresponse are given. The use of estimated response probabilities in constructing regression estimators is investigated. Several closely related adjustment procedures are applied to the Survey of Income and Program Participation conducted by the U. S. Census Bureau.

ESTIMATION OF THE DIETARY USUAL INTAKE DISTRIBUTION
4:00 p.m. Wednesday, October 16, 1996
Room 102, Zachry

A person's usual intake of a dietary component is the long run average daily consumption of that component. The daily intake for an individual can be modeled as the usual intake plus a deviation, where the deviation can be treated as measurement error. The distribution of usual intake is important information for policymakers. Using survey data on daily intake, the distribution of usual intake is estimated under the assumption that it is possible to transform intakes to normality and that at least two daily observations are available for a subsample of the sample of individuals.

ESTIMATORS FOR AUTOREGRESSIVE PROCESSES WITH A ROOT NEAR ONE
4:00 p.m. Thursday, October 17, 1996
Room 150, Blocker

Estimators for the parameters of autoregressive time series are compared, emphasizing processes with a unit root or a root close to one. Economic time series often exhibit behavior that can be approximated by such processes. Estimators that are nearly median unbiased for the parameter of the first order process with a parameter near one are presented. These estimators have smaller mean square errors than ordinary least squares for processes with a root near one and have mean square errors close to those of ordinary least squares for other parameter configurations.

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