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MA
2010
Springer
135views Communications» more  MA 2010»
13 years 3 months ago
Nonparametric comparison of regression functions
In this work we provide a new methodology for comparing regression functions m1 and m2 from two samples. Since apart from smoothness no other (parametric) assumptions are required...
Ramidha Srihera, Winfried Stute
JMLR
2010
118views more  JMLR 2010»
12 years 11 months ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell
CSDA
2006
87views more  CSDA 2006»
13 years 4 months ago
Choice of B-splines with free parameters in the flexible discriminant analysis context
Flexible discriminant analysis (FDA) is a general methodology which aims at providing tools for multigroup non linear classification. It consists in a nonparametric version of dis...
Christelle Reynès, Robert Sabatier, Nicolas...
JMLR
2011
167views more  JMLR 2011»
12 years 11 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
CSSC
2008
84views more  CSSC 2008»
13 years 4 months ago
Nonparametric Regression as an Example of Model Choice
Nonparametric regression can be considered as a problem of model choice. In this paper we present the results of a simulation study in which several nonparametric regression techn...
Laurie Davies, Ursula Gather, Henrike Weinert