JSM 2005 - Toronto

Abstract #302412

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 46
Type: Invited
Date/Time: Sunday, August 7, 2005 : 4:00 PM to 5:50 PM
Sponsor: Section on Statistics and the Environment
Abstract - #302412
Title: Some New Spatial Statistical Models for Stream Networks
Author(s): Jay Ver Hoef*+
Companies: Alaska Department of Fish and Game
Address: 1300 College Road, Fairbanks, AK, 99701-1599, United States
Keywords: geostatistics ; kriging ; moving average ; spatial statistics
Abstract:

Models for spatial autocorrelation depend on the distance and direction separating two locations and are constrained so that for all possible sets of locations, the covariance matrices implied from the models remain nonnegative definite. Although there are extensive sets of families of models for two-dimensional space, few models have been developed for stream networks. The only known model valid for stream networks is an exponential model, and it is based on stream distance. Even this model may not be appropriate when considering flow characteristics of streams. Recent research has shown that moving-average functions, also known as kernel convolutions, may be used to generate a large class of valid, flexible models in two dimensions. This paper develops moving average models for stream networks.

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Revised March 2005