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Instability and Change Detection in Exponential Families and Generalized Linear Models, with a Study of Atlantic Tropical Storms : Volume 1, Issue 1 (21/03/2014)

By Lu, Y.

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Book Id: WPLBN0004020094
Format Type: PDF Article :
File Size: Pages 31
Reproduction Date: 2015

Title: Instability and Change Detection in Exponential Families and Generalized Linear Models, with a Study of Atlantic Tropical Storms : Volume 1, Issue 1 (21/03/2014)  
Author: Lu, Y.
Volume: Vol. 1, Issue 1
Language: English
Subject: Science, Nonlinear, Processes
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Chatterjee, S., & Lu, Y. (2014). Instability and Change Detection in Exponential Families and Generalized Linear Models, with a Study of Atlantic Tropical Storms : Volume 1, Issue 1 (21/03/2014). Retrieved from

Description:, Seattle, Washington, USA. Exponential family statistical distributions, including the well-known Normal, Binomial, Poisson, and exponential distributions, are overwhelmingly used in data analysis. In the presence of covariates, an exponential family distributional assumption for the response random variables results in a generalized linear model. However, it is rarely ensured that the parameters of the assumed distributions are stable through the entire duration of data collection process. A failure of stability leads to nonsmoothness and nonlinearity in the physical processes that drive the data under. In this paper, we propose testing for stability of parameters of exponential family distributions and generalized linear models. A rejection of the hypothesis of stable parameters leads to change detection. We derive the related likelihood ratio test statistic. We compare the performance of this test statistic to the popular Normal distributional assumption dependent cumulative sum (Gaussian-CUSUM) statistic in change detection problems. We study Atlantic tropical storms using the techniques developed here, to understand whether the nature of these tropical storms has remained stable over the last few decades.

Instability and change detection in exponential families and generalized linear models, with a study of Atlantic tropical storms

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