Title :
Mixture of nonlinear models: a Bayesian fit for Principal Curves
Author :
Delicado, Pedro ; Smrekar, Marcelo
Author_Institution :
Univ. Politecnica de Catalunya, Barcelona
Abstract :
Principal curves are smooth parametric curves passing through the "middle" of a non-elliptical multivariate data set. We model the probability distribution of this kind of data as a mixture of simple nonlinear models and use MCMC techniques to fit the mixture model.
Keywords :
Bayes methods; computational geometry; curve fitting; statistical distributions; Bayesian fit; nonelliptical multivariate data set; nonlinear mixture model; principal curves; probability distribution; smooth parametric curves; Bayesian methods; Equations; Multidimensional systems; Neural networks; Parameter estimation; Principal component analysis; Probability distribution; Proposals; Random variables; Scattering parameters;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4370954
