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ESTIMATION OF LOCAL POWER LAW PROCESSES
Knut Solna
University of Utah
April 9, JWB 208, 305 p.m.
Abstract
We present a new approach for analyzing local
power law processes and apply it to
temperature measurements from the upper atmosphere.
We segment the data and use the wavelet scale
spectrum to estimate the parameters of the power
law, the scale factor and the exponent. These
parameters vary from segment to segment.
Part of this variation is due to the non-stationarity
of the data. Another part is due to estimation errors
that depend on the segmentation. In this paper
show how to remove effectively these segmentation
dependent variations.
The temperature data that are expected
to have Kolmogorov power law spectra. We find
that there are significant fluctuations about the
Kolmogorov law.