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Change‐point methods for Weibull models with applications to detection of trends in extreme temperatures
Author(s) -
Jandhyala V. K.,
Fotopoulos S. B.,
Evaggelopoulos N.
Publication year - 1999
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/(sici)1099-095x(199909/10)10:5<547::aid-env359>3.0.co;2-y
Subject(s) - weibull distribution , statistic , statistics , maximum likelihood , change detection , econometrics , mathematics , scale (ratio) , scale parameter , point (geometry) , shape parameter , computer science , geography , artificial intelligence , geometry , cartography
We develop change‐point methodology for identifying dynamic trends in the scale and shape parameters of a Weibull distribution. The methodology includes asymptotics of the likelihood ratio statistic for detecting unknown changes in the parameters as well as asymptotics of the maximum likelihood estimate of the unknown change‐point. The developed methodology is applied to detect dynamic changes in the minimum temperatures of Uppsala, Sweden. Copyright © 1999 John Wiley & Sons, Ltd.