Download or read book Some Contributions to Bayesian Nonparametric Inference written by and published by . This book was released on 1994 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Some Contributions to Bayesian Nonparametric Statistical Inference written by Albert Yee-Lap and published by . This book was released on 1978 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Some Contributions to Bayesian Nonparametric Statistical Inference written by Albert Yee-Lap Lo and published by . This book was released on 1978 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Contributions to Bayesian Statistical Analysis written by Milovan Krnjajić and published by . This book was released on 2005 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Bayesian Inference written by Jean-Pierre Florens and published by Springer. This book was released on 2024-07-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of unpublished papers written by Jean-Marie Rolin (with several co-authors) on nonparametric bayesian estimation. Jean-Marie was professor of statistics at University of Louvain and died on November 5th, 2018. He made important contributions in mathematical statistics with applications to different fields like econometrics or biometrics. These papers cover a variety of topics, including: • Mathematical structure of the Bayesian model and main concepts (sufficiency, analarity, invariance...) • Representation of the Dirichlet processes and of the associated Polya urn model and applications to nonparametric bayesian analysis. • Contributions on duration models and on their non parametric bayesian treatment.

Download or read book Nonparametric Bayesian Inference in Biostatistics written by Riten Mitra and published by Springer. This book was released on 2015-07-25 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters cover: clinical trials, spatial inference, proteomics, genomics, clustering, survival analysis and ROC curve.

Download or read book bayesian nonparametric inference written by stephen walker and published by . This book was released on 1997 with total page 50 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Nonparametric Inference for Random Distributions and Related Functions written by Stephen Walker and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fundamentals of Nonparametric Bayesian Inference written by Subhashis Ghosal and published by Cambridge University Press. This book was released on 2017-06-26 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.

Download or read book Some Contributions to Nonparametric Bayesian Methods written by Junjing Lin and published by . This book was released on 2015 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thesis makes contributions to the area of nonparametric Bayesian methods and applications in two distinct subject areas. One is about classification problems in machine learning. The other is on network meta-analysis in the field of clinical trials. We start by introducing some basic facts about Dirichlet distributions and Dirichlet processes. Nonparametric Bayesian methods and models and their construction follows. We then provide a survey of the existing Markov chain Monte Carlo inference algorithms for Dirichlet Process Mixture models (DPMM), which is followed by a detailed description of these methods to the application problems.

Download or read book Bayesian Nonparametric Data Analysis written by Peter Müller and published by Springer. This book was released on 2015-06-17 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.

Download or read book Bayesian Nonparametric Inference in Reliability Theory written by Purushottam Laud and published by . This book was released on 1977 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Nonparametric Inference for Competing Risks Data written by Xiaolin Fan and published by . This book was released on 2008 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On New Constructive Tools in Bayesian Nonparametric Inference written by Luai Al Labadi and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The Bayesian nonparametric inference requires the construction of priors on infinite dimensional spaces such as the space of cumulative distribution functions and the space of cumulative hazard functions. Well-known priors on the space of cumulative distribution functions are the Dirichlet process, the two-parameter Poisson-Dirichlet process and the beta-Stacy process. On the other hand, the beta process is a popular prior on the space of cumulative hazard functions. This thesis is divided into three parts. In the first part, we tackle the problem of sampling from the above mentioned processes. Sampling from these processes plays a crucial role in many applications in Bayesian nonparametric inference. However, having exact samples from these processes is impossible. The existing algorithms are either slow or very complex and may be difficult to apply for many users. We derive new approximation techniques for simulating the above processes. These new approximations provide simple, yet efficient, procedures for simulating these important processes. We compare the efficiency of the new approximations to several other well-known approximations and demonstrate a significant improvement. In the second part, we develop explicit expressions for calculating the Kolmogorov, Levy and Cramer-von Mises distances between the Dirichlet process and its base measure. The derived expressions of each distance are used to select the concentration parameter of a Dirichlet process. We also propose a Bayesain goodness of fit test for simple and composite hypotheses for non-censored and censored observations. Illustrative examples and simulation results are included. Finally, we describe the relationship between the frequentist and Bayesian nonparametric statistics. We show that, when the concentration parameter is large, the two-parameter Poisson-Dirichlet process and its corresponding quantile process share many asymptotic pr operties with the frequentist empirical process and the frequentist quantile process. Some of these properties are the functional central limit theorem, the strong law of large numbers and the Glivenko-Cantelli theorem.

Download or read book Implementation of Bayesian Nonparametric Inference Based on Beta Processes written by Paul Damien and published by . This book was released on 1994 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bayesian Nonparametric Inference for Queueing Systems written by Moritz von Rohrscheidt and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Nonparametric Bayesian Inference written by Peter Müller and published by . This book was released on 2013 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt: