This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 525
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract - #308508
Title: Wavelet Analysis in Spatial Interpolation of High Frequency Monitoring Data
Author(s): Michael Stein and Xiaohui Chang*+
Companies: The University of Chicago and The University of Chicago
Address: 5734 S University Ave , Chicago, IL, 60615,
Keywords: wavelet analysis ; space - time process ; meteorology ; spectral analysis ; monitoring data
Abstract:

Spectral analysis of spatial temporal data has the difficulty of capturing and explaining infrequent local changes that are often observed in meteorological data. We propose a wavelet based approach to explain the sudden but strong local changes seen in a high frequency monitoring dataset, also hoping that the covariance structure of data after wavelet transform is simpler and easier to analyze.

The data were collected through the Atmospheric Radiation Measurement Program and it includes high frequency measurements of many meteorological variables. Under a parametric framework, our Simple Scale Model does just as well as more complicated models using Fourier analysis.

In order to capture the asymmetry pattern that is usually associated with meteorological data, more elaborate models are also proposed.


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