Multivariate Bayesian statistics : models for source separation and signal unmixing /

Bibliographic Details
Main Author:	Rowe, Daniel B.
Corporate Author:	Taylor & Francis
Format:	eBook
Language:	English
Published:	Boca Raton : Chapman & Hall/CRC, ©2003.
Subjects:	Bayesian statistical decision theory. Multivariate analysis. Bayes Theorem Multivariate Analysis Théorie de la décision bayésienne. Analyse multivariée. Théorème de Bayes. MATHEMATICS > Probability & Statistics > Bayesian Analysis. Bayesian statistical decision theory Multivariate analysis Methode van Bayes. Multivariate analyse. Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Introduction; Part l: FUNDAMENTALS; STATISTICAL DISTRIBUTIONS; Scalar Distributions; Vector Distributions; Matrix Distributions; INTRODUCTORY BAYESIAN STATISTICS; Discrete Scalar Variables; Continuous Scalar Variables; Continuous Vector Variables; Continuous Matrix Variables; PRIOR DISTRIBUTIONS; Vague Priors; Conjugate Priors; Generaliz ed Priors; Correlation Priors; HYPERPARAMETER ASSESSMENT; Introduction; Binomial Likelihood; Scalar Normal Likelihood; Multivariate Normal Likelihood; Matrix Normal Likelihood; BAYESIAN ESTIMATION METHODS; Marginal Posterior Mean; Maximum a Posteriori; Advantages of ICM over Gibbs Sampling; Advantages of Gibbs Sampling over ICM; REGRESSION; Introduction; Normal Samples; Simple Linear Regression; Multiple Linear Regression; Multivariate Linear Regression; ; Part II: II Models; BAYESIAN REGRESSION; Introduction; The Bayesian Regression.
Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; BAYESIAN FACTOR ANALYSIS; Introduction; The Bayesian Factor Analysis Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; BAYESIAN SOURCE SEPARATION; Introduction; Source Separation Model; Source Separation Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; UNOBSERVABLE AND OBSERVABLE SOURCE SEPARATION; Introduction; Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and.
Inference; Interpretation; Discussion; FMRI CASE STUDY; Introduction; Model; Priors and Posterior; Estimation and Inference; Simulated FMRI Experiment; Real FMRI Experiment; FMRI Conclusion; ; Part III: Generalizations; DELAYED SOURCES AND DYNAMIC COEFFICIENTS; Introduction; Model; Delayed Constant Mixing; Delayed Nonconstant Mixing; Instantaneous Nonconstant Mixing; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; CORRELATED OBSERVATION AND SOURCE VECTORS; Introduction; Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Posterior Conditionals; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; CONCLUSION; Appendix A FMRI Activation Determination; Appendix B FMRI Hyperparameter.