We consider additive models fitting and inference when the response variable is a sample extreme. Non-linear covariate effects are handled using the mixed model representation of penalised splines. A fitting algorithm based on likelihood approximations is derived. The efficacy of the resulting methodology is demonstrated via application to simulated and real data.

Mixed model-based additive models for sample extremes

PADOAN, SIMONE;
2008

Abstract

We consider additive models fitting and inference when the response variable is a sample extreme. Non-linear covariate effects are handled using the mixed model representation of penalised splines. A fitting algorithm based on likelihood approximations is derived. The efficacy of the resulting methodology is demonstrated via application to simulated and real data.
2008
Padoan, Simone; M. P., Wand
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/3855296
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