Overview
- Editors:
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Emanuel Parzen
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Department of Statistics, Texas A & M University, College Station, USA
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Table of contents (17 papers)
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Front Matter
Pages N2-viii
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- Craig F. Ansley, Robert Kohn
Pages 9-37
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- A. C. Harvey, C. R. McKenzie
Pages 108-133
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- Melvin J. Hinich, Warren E. Weber
Pages 134-157
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- Donald W. Marquardt, Sherry K. Acuff
Pages 211-223
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- Robert B. Miller, Osvaldo Ferreiro
Pages 251-275
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- Anthony D. Thrall, C. Shepherd Burton
Pages 346-352
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About this book
With the support of the Office of Naval Research Program on Statistics and Probability (Dr. Edward J. Wegman, Director), The Department of Statistics at Texas A&M University hosted a Symposium on Time Series Analysis of Irregularly Observed Data during the period February 10-13, 1983. The symposium aimed to provide a review of the state of the art, define outstanding problems for research by theoreticians, transmit to practitioners recently developed algorithms, and stimulate interaction between statisticians and researchers in subject matter fields. Attendance was limited to actively involved researchers. This volume contains refereed versions of the papers presented at the Symposium. We would like to express our appreciation to the many colleagues and staff members whose cheerful help made the Symposium a successful happening which was enjoyed socially and intellectually by all participants. I would like to especially thank Dr. Donald W. Marquardt whose interest led me to undertake to organize this Symposium. This volume is dedicated to the world wide community of researchers who develop and apply methods of statistical analysis of time series. r:;) \J Picture Caption Participants in Symposium on Time Series Analysis of Irregularly Observed Data at Texas A&M University, College Station, Texas, February 10-13, 1983 First Row: Henry L. Gray, D. W. Marquardt, P. M. Robinson, Emanuel Parzen, Julia Abrahams, E. Masry, H. L. Weinert, R. H. Shumway.
Editors and Affiliations
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Department of Statistics, Texas A & M University, College Station, USA
Emanuel Parzen