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JMLR
2010

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Dirichlet Process Mixtures of Generalized Linear Models

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Dirichlet Process Mixtures of Generalized Linear Models

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We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models a response variable locally by a generalized linear model. We give conditions for the existence and asymptotic unbiasedness of the DP-GLM regression mean function estimate; we then give a practical example for when those conditions hold. We evaluate DP-GLM on several data sets, comparing it to modern methods of nonparametric regression including regression trees and Gaussian processes.

Lauren Hannah, David M. Blei, Warren B. Powell

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Generalized Linear Model | JMLR 2010 | Nonparametric Regression | Regression Trees |

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Added	19 May 2011
Updated	19 May 2011
Type	Journal
Year	2010
Where	JMLR
Authors	Lauren Hannah, David M. Blei, Warren B. Powell

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