Multivariate Dispersion, Central Regions, and Depth

Multivariate Dispersion, Central Regions, and Depth PDF Author: Karl Mosler
Publisher: Springer Science & Business Media
ISBN: 1461300452
Category : Mathematics
Languages : en
Pages : 303

Get Book Here

Book Description
This book has many applications to stochastic comparison problems in economics and other fields. It covers theory of lift zonoids and demonstrates its usefulness in multivariate analysis, an informal introduction to basic ideas, and a comprehensive investigation into the theory, as well as various applications of the lift zonoid approach and may be separately studied. Readers are assumed to have a firm grounding in probability at the graduate level.

Multivariate Dispersion, Central Regions, and Depth

Multivariate Dispersion, Central Regions, and Depth PDF Author: Karl Mosler
Publisher: Springer Science & Business Media
ISBN: 1461300452
Category : Mathematics
Languages : en
Pages : 303

Get Book Here

Book Description
This book has many applications to stochastic comparison problems in economics and other fields. It covers theory of lift zonoids and demonstrates its usefulness in multivariate analysis, an informal introduction to basic ideas, and a comprehensive investigation into the theory, as well as various applications of the lift zonoid approach and may be separately studied. Readers are assumed to have a firm grounding in probability at the graduate level.

Multivariate Dispersion, Central Regions, and Depth

Multivariate Dispersion, Central Regions, and Depth PDF Author: Karl Mosler
Publisher:
ISBN: 9781461300465
Category :
Languages : en
Pages : 312

Get Book Here

Book Description


Case Studies in Bayesian Statistics

Case Studies in Bayesian Statistics PDF Author: Constantine Gatsonis
Publisher: Springer
ISBN: 1461220785
Category : Mathematics
Languages : en
Pages : 384

Get Book Here

Book Description
This volume contains invited case studies with the accompanying discussion as well as contributed papers selected by a refereeing process of 6th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University in October, 2001.

Multivariate Nonparametric Methods with R

Multivariate Nonparametric Methods with R PDF Author: Hannu Oja
Publisher: Springer Science & Business Media
ISBN: 1441904689
Category : Mathematics
Languages : en
Pages : 239

Get Book Here

Book Description
This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 norm is just replaced by different L1 norms, observation vectors are replaced by spatial signs and ranks, and so on. A unified methodology starting with the simple one-sample multivariate location problem and proceeding to the general multivariate multiple linear regression case is presented. Companion estimates and tests for scatter matrices are considered as well. The R package MNM is available for computation of the procedures. This monograph provides an up-to-date overview of the theory of multivariate nonparametric methods based on spatial signs and ranks. The classical book by Puri and Sen (1971) uses marginal signs and ranks and different type of L1 norm. The book may serve as a textbook and a general reference for the latest developments in the area. Readers are assumed to have a good knowledge of basic statistical theory as well as matrix theory. Hannu Oja is an academy professor and a professor in biometry in the University of Tampere. He has authored and coauthored numerous research articles in multivariate nonparametrical and robust methods as well as in biostatistics.

Data Depth

Data Depth PDF Author: Regina Y. Liu
Publisher: American Mathematical Soc.
ISBN: 0821835963
Category : Mathematics
Languages : en
Pages : 264

Get Book Here

Book Description
The book is a collection of some of the research presented at the workshop of the same name held in May 2003 at Rutgers University. The workshop brought together researchers from two different communities: statisticians and specialists in computational geometry. The main idea unifying these two research areas turned out to be the notion of data depth, which is an important notion both in statistics and in the study of efficiency of algorithms used in computational geometry. Many of the articles in the book lay down the foundations for further collaboration and interdisciplinary research. Information for our distributors: Co-published with the Center for Discrete Mathematics and Theoretical Computer Science beginning with Volume 8. Volumes 1-7 were co-published with the Association for Computer Machinery (ACM).

Combining Soft Computing and Statistical Methods in Data Analysis

Combining Soft Computing and Statistical Methods in Data Analysis PDF Author: Christian Borgelt
Publisher: Springer Science & Business Media
ISBN: 3642147461
Category : Technology & Engineering
Languages : en
Pages : 640

Get Book Here

Book Description
Over the last forty years there has been a growing interest to extend probability theory and statistics and to allow for more flexible modelling of imprecision, uncertainty, vagueness and ignorance. The fact that in many real-life situations data uncertainty is not only present in the form of randomness (stochastic uncertainty) but also in the form of imprecision/fuzziness is but one point underlining the need for a widening of statistical tools. Most such extensions originate in a "softening" of classical methods, allowing, in particular, to work with imprecise or vague data, considering imprecise or generalized probabilities and fuzzy events, etc. About ten years ago the idea of establishing a recurrent forum for discussing new trends in the before-mentioned context was born and resulted in the first International Conference on Soft Methods in Probability and Statistics (SMPS) that was held in Warsaw in 2002. In the following years the conference took place in Oviedo (2004), in Bristol (2006) and in Toulouse (2008). In the current edition the conference returns to Oviedo. This edited volume is a collection of papers presented at the SMPS 2010 conference held in Mieres and Oviedo. It gives a comprehensive overview of current research into the fusion of soft methods with probability and statistics.

Parametric and Nonparametric Inference from Record-Breaking Data

Parametric and Nonparametric Inference from Record-Breaking Data PDF Author: Sneh Gulati
Publisher: Springer Science & Business Media
ISBN: 0387215492
Category : Mathematics
Languages : en
Pages : 123

Get Book Here

Book Description
By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.

Estimation in Conditionally Heteroscedastic Time Series Models

Estimation in Conditionally Heteroscedastic Time Series Models PDF Author: Daniel Straumann
Publisher: Springer Science & Business Media
ISBN: 3540269789
Category : Business & Economics
Languages : en
Pages : 239

Get Book Here

Book Description
In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies.

Convex Bodies: The Brunn–Minkowski Theory

Convex Bodies: The Brunn–Minkowski Theory PDF Author: Rolf Schneider
Publisher: Cambridge University Press
ISBN: 1107601010
Category : Mathematics
Languages : en
Pages : 759

Get Book Here

Book Description
A complete presentation of a central part of convex geometry, from basics for beginners, to the exposition of current research.

Statistical Matching

Statistical Matching PDF Author: Susanne Rässler
Publisher: Springer Science & Business Media
ISBN: 1461300533
Category : Mathematics
Languages : en
Pages : 260

Get Book Here

Book Description
Government policy questions and media planning tasks may be answered by this data set. It covers a wide range of different aspects of statistical matching that in Europe typically is called data fusion. A book about statistical matching will be of interest to researchers and practitioners, starting with data collection and the production of public use micro files, data banks, and data bases. People in the areas of database marketing, public health analysis, socioeconomic modeling, and official statistics will find it useful.