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SMA
2010
ACM
181views Solid Modeling» more  SMA 2010»
8 years 5 months ago
Threshold selection in jump-discriminant filter for discretely observed jump processes
Threshold estimation is one of the useful techniques in the inference for jump-type stochastic processes from discrete observations. In this method, a jump-discriminant filter is ...
Yasutaka Shimizu
SMA
2010
ACM
192views Solid Modeling» more  SMA 2010»
8 years 5 months ago
Infinitesimally Robust estimation in general smoothly parametrized models
Abstract The aim of the paper is to give a coherent account of the robustness approach based on shrinking neighborhoods in the case of i.i.d. observations, and add some theoretical...
Matthias Kohl, Peter Ruckdeschel, Helmut Rieder
SMA
2010
ACM
200views Solid Modeling» more  SMA 2010»
8 years 5 months ago
Influence functions of the Spearman and Kendall correlation measures
Abstract Nonparametric correlation estimators as the Kendall and Spearman correlation are widely used in the applied sciences. They are often said to be robust, in the sense of bei...
Christophe Croux, Catherine Dehon
SMR
2011
302views Solid Modeling» more  SMR 2011»
8 years 5 months ago
Preparing for a new era
Gerardo Canfora, Darren Dalcher, David Raffo
SMA
2011
ACM
288views Solid Modeling» more  SMA 2011»
8 years 5 months ago
Robust variable selection with application to quality of life research
Andreas Alfons, Wolfgang E. Baaske, Peter Filzmose...
SMA
2011
ACM
265views Solid Modeling» more  SMA 2011»
8 years 5 months ago
Modeling individual migraine severity with autoregressive ordered probit models
This paper considers the problem of modeling migraine severity assessments and their dependence on weather and time characteristics. We take on the viewpoint of a patient who is i...
Claudia Czado, Anette Heyn, Gernot Müller
COMPLEXITY
2010
173views more  COMPLEXITY 2010»
8 years 5 months ago
Signal-regulated systems and networks
The paper presents the use of signal regulatory networks, a biologically-inspired model based on gene regulatory networks. Signal regulatory networks are a way of understanding a ...
Terence L. van Zyl, Elizabeth Marie Ehlers
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