Skip to main content

Generalized additive modelling of sample extremes

Buy Article:

$51.00 plus tax (Refund Policy)



We describe smooth non-stationary generalized additive modelling for sample extremes, in which spline smoothers are incorporated into models for exceedances over high thresholds. Fitting is by maximum penalized likelihood estimation, with uncertainty assessed by using differences of deviances and bootstrap simulation. The approach is illustrated by using data on extreme winter temperatures in the Swiss Alps, analysis of which shows strong influence of the north Atlantic oscillation. Benefits of the new approach are flexible and appropriate modelling of extremes, more realistic assessment of estimation uncertainty and the accommodation of complex dependence patterns.

Keywords: Bootstrap; Generalized Pareto distribution; Generalized additive model; Natural cubic spline; North Atlantic oscillation; Parameter orthogonality; Peaks over threshold; Penalized likelihood; Statistics of extremes; Temperature data

Document Type: Research Article


Affiliations: 1: Eidgenössiche Technische Hochschule, Zürich, Switzerland 2: Swiss Federal Institute of Technology, Lausanne, Switzerland

Publication date: January 1, 2005


Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more