We review the concept of locally linear regression and its relationship to Diday’s Nuées Dynamiques and to tree-structured linear regression. We describe the calibration problem in microarray analysis and propose a Bayesian approach based on tree-structured linear regression. Using the proposed approach, we analyze a subset of a large data set from an Affymetrix microarray calibration experiment. In this example, a tree-structured regression model outperforms a multiple regression model. We calculated 95% Credible Intervals for a sample of the data, obtaining reasonably good results. Future research will consider and compare several other approaches to locally linear regression.

Locally linear regression and the calibration problem for Micro-Array analysis

Villalobos, Isadora Antoniano
Formal Analysis
;
2007

Abstract

We review the concept of locally linear regression and its relationship to Diday’s Nuées Dynamiques and to tree-structured linear regression. We describe the calibration problem in microarray analysis and propose a Bayesian approach based on tree-structured linear regression. Using the proposed approach, we analyze a subset of a large data set from an Affymetrix microarray calibration experiment. In this example, a tree-structured regression model outperforms a multiple regression model. We calculated 95% Credible Intervals for a sample of the data, obtaining reasonably good results. Future research will consider and compare several other approaches to locally linear regression.
2007
9783540735588
9783540735601
Brito, Paula; Cucumel, Guy; Bertrand, Patrice; De Carvalho, Francisco
Selected contributions in data analysis and classification
Ciampi, Antonio; Rich, Benjamin; Dyachenko, Alina; Villalobos, Isadora Antoniano; Murie, Carl; Nadon, Robert
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/4006672
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