Multivariate Bayesian statistics : models for source separation and signal unmixing /: models for source separation and signal unmixing. (©2003)

• Record Type: Book
• Further Information: Note: Daniel B. Rowe.
• Other Names: Rowe, Daniel B
• 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 Assessment; Bibliography; Index
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2003
• Copyright Date: 2003
• Extent: 1 online resource (xx, 329 pages), illustrations
• Subjects: 519.5/42; Bayesian statistical decision theory; Multivariate analysis; Bayes Theorem; Multivariate Analysis; MATHEMATICS -- Probability & Statistics -- Bayesian Analysis; Bayesian statistical decision theory; Multivariate analysis; Methode van Bayes; Multivariate analyse; Electronic books
• Languages: English
• ISBNs: 1584883189; 9781584883180; 1420035266; 9781420035261
• Notes: Note: Includes bibliographical references.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.