 |
| Titel |
Instability and change detection in exponential families and generalized linear models, with a study of Atlantic tropical storms |
| VerfasserIn |
Y. Lu, S. Chatterjee |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
2198-5634
|
| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics Discussions ; 1, no. 1 ; Nr. 1, no. 1 (2014-03-21), S.371-401 |
| Datensatznummer |
250115080
|
| Publikation (Nr.) |
 copernicus.org/npgd-1-371-2014.pdf |
|
|
|
|
|
| Zusammenfassung |
| 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. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|