Nonparametric Analysis Of Univariate Heavy Tailed Data

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Nonparametric Analysis of Univariate Heavy-Tailed Data

Natalia Markovich
Nonparametric Analysis of Univariate Heavy Tailed Data Book PDF

Author : Natalia Markovich
Publisher : John Wiley & Sons
Page : 336 pages
File Size : 43,9 Mb
Release : 2008-03-11
Category : Mathematics
ISBN : 0470723599

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Nonparametric Analysis of Univariate Heavy-Tailed Data by Natalia Markovich Pdf

Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution. The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function. Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.

Nonparametric Statistics

Patrice Bertail,Delphine Blanke,Pierre-André Cornillon,Eric Matzner-Løber
Nonparametric Statistics Book PDF

Author : Patrice Bertail,Delphine Blanke,Pierre-André Cornillon,Eric Matzner-Løber
Publisher : Springer
Page : 390 pages
File Size : 55,6 Mb
Release : 2019-03-08
Category : Mathematics
ISBN : 9783319969411

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Nonparametric Statistics by Patrice Bertail,Delphine Blanke,Pierre-André Cornillon,Eric Matzner-Løber Pdf

This volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data. The International Society for Nonparametric Statistics is uniquely global, and its international conferences are intended to foster the exchange of ideas and the latest advances among researchers from around the world, in cooperation with established statistical societies such as the Institute of Mathematical Statistics, the Bernoulli Society and the International Statistical Institute. The 3rd ISNPS conference in Avignon attracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge.

Permutation Tests for Complex Data

Fortunato Pesarin,Luigi Salmaso
Permutation Tests for Complex Data Book PDF

Author : Fortunato Pesarin,Luigi Salmaso
Publisher : John Wiley & Sons
Page : 448 pages
File Size : 47,6 Mb
Release : 2010-02-25
Category : Mathematics
ISBN : 0470689528

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Permutation Tests for Complex Data by Fortunato Pesarin,Luigi Salmaso Pdf

Complex multivariate testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. As a result, modern statistics needs permutation testing for complex data with low sample size and many variables, especially in observational studies. The Authors give a general overview on permutation tests with a focus on recent theoretical advances within univariate and multivariate complex permutation testing problems, this book brings the reader completely up to date with today’s current thinking. Key Features: Examines the most up-to-date methodologies of univariate and multivariate permutation testing. Includes extensive software codes in MATLAB, R and SAS, featuring worked examples, and uses real case studies from both experimental and observational studies. Includes a standalone free software NPC Test Release 10 with a graphical interface which allows practitioners from every scientific field to easily implement almost all complex testing procedures included in the book. Presents and discusses solutions to the most important and frequently encountered real problems in multivariate analyses. A supplementary website containing all of the data sets examined in the book along with ready to use software codes. Together with a wide set of application cases, the Authors present a thorough theory of permutation testing both with formal description and proofs, and analysing real case studies. Practitioners and researchers, working in different scientific fields such as engineering, biostatistics, psychology or medicine will benefit from this book.

Dynamic Models for Volatility and Heavy Tails

Andrew C. Harvey
Dynamic Models for Volatility and Heavy Tails Book PDF

Author : Andrew C. Harvey
Publisher : Cambridge University Press
Page : 281 pages
File Size : 48,5 Mb
Release : 2013-04-22
Category : Business & Economics
ISBN : 9781107034723

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Dynamic Models for Volatility and Heavy Tails by Andrew C. Harvey Pdf

The volatility of financial returns changes over time and, for the last thirty years, Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models have provided the principal means of analyzing, modeling and monitoring such changes. Taking into account that financial returns typically exhibit heavy tails - that is, extreme values can occur from time to time - Andrew Harvey's new book shows how a small but radical change in the way GARCH models are formulated leads to a resolution of many of the theoretical problems inherent in the statistical theory. The approach can also be applied to other aspects of volatility. The more general class of Dynamic Conditional Score models extends to robust modeling of outliers in the levels of time series and to the treatment of time-varying relationships. The statistical theory draws on basic principles of maximum likelihood estimation and, by doing so, leads to an elegant and unified treatment of nonlinear time-series modeling.

Meta Analysis

Elena Kulinskaya,Stephan Morgenthaler,Robert G. Staudte
Meta Analysis Book PDF

Author : Elena Kulinskaya,Stephan Morgenthaler,Robert G. Staudte
Publisher : John Wiley & Sons
Page : 282 pages
File Size : 41,9 Mb
Release : 2008-04-15
Category : Mathematics
ISBN : 0470985526

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Meta Analysis by Elena Kulinskaya,Stephan Morgenthaler,Robert G. Staudte Pdf

Meta Analysis: A Guide to Calibrating and Combining Statistical Evidence acts as a source of basic methods for scientists wanting to combine evidence from different experiments. The authors aim to promote a deeper understanding of the notion of statistical evidence. The book is comprised of two parts – The Handbook, and The Theory. The Handbook is a guide for combining and interpreting experimental evidence to solve standard statistical problems. This section allows someone with a rudimentary knowledge in general statistics to apply the methods. The Theory provides the motivation, theory and results of simulation experiments to justify the methodology. This is a coherent introduction to the statistical concepts required to understand the authors’ thesis that evidence in a test statistic can often be calibrated when transformed to the right scale.

Spatial Statistics and Spatio-Temporal Data

Michael Sherman
Spatial Statistics and Spatio Temporal Data Book PDF

Author : Michael Sherman
Publisher : John Wiley & Sons
Page : 190 pages
File Size : 40,5 Mb
Release : 2011-01-06
Category : Mathematics
ISBN : 9780470974926

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Spatial Statistics and Spatio-Temporal Data by Michael Sherman Pdf

In the spatial or spatio-temporal context, specifying the correct covariance function is fundamental to obtain efficient predictions, and to understand the underlying physical process of interest. This book focuses on covariance and variogram functions, their role in prediction, and appropriate choice of these functions in applications. Both recent and more established methods are illustrated to assess many common assumptions on these functions, such as, isotropy, separability, symmetry, and intrinsic correlation. After an extensive introduction to spatial methodology, the book details the effects of common covariance assumptions and addresses methods to assess the appropriateness of such assumptions for various data structures. Key features: An extensive introduction to spatial methodology including a survey of spatial covariance functions and their use in spatial prediction (kriging) is given. Explores methodology for assessing the appropriateness of assumptions on covariance functions in the spatial, spatio-temporal, multivariate spatial, and point pattern settings. Provides illustrations of all methods based on data and simulation experiments to demonstrate all methodology and guide to proper usage of all methods. Presents a brief survey of spatial and spatio-temporal models, highlighting the Gaussian case and the binary data setting, along with the different methodologies for estimation and model fitting for these two data structures. Discusses models that allow for anisotropic and nonseparable behaviour in covariance functions in the spatial, spatio-temporal and multivariate settings. Gives an introduction to point pattern models, including testing for randomness, and fitting regular and clustered point patterns. The importance and assessment of isotropy of point patterns is detailed. Statisticians, researchers, and data analysts working with spatial and space-time data will benefit from this book as well as will graduate students with a background in basic statistics following courses in engineering, quantitative ecology or atmospheric science.

Batch Effects and Noise in Microarray Experiments

Andreas Scherer
Batch Effects and Noise in Microarray Experiments Book PDF

Author : Andreas Scherer
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 51,7 Mb
Release : 2009-11-03
Category : Science
ISBN : 0470685999

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Batch Effects and Noise in Microarray Experiments by Andreas Scherer Pdf

Batch Effects and Noise in Microarray Experiments: Sources and Solutions looks at the issue of technical noise and batch effects in microarray studies and illustrates how to alleviate such factors whilst interpreting the relevant biological information. Each chapter focuses on sources of noise and batch effects before starting an experiment, with examples of statistical methods for detecting, measuring, and managing batch effects within and across datasets provided online. Throughout the book the importance of standardization and the value of standard operating procedures in the development of genomics biomarkers is emphasized. Key Features: A thorough introduction to Batch Effects and Noise in Microrarray Experiments. A unique compilation of review and research articles on handling of batch effects and technical and biological noise in microarray data. An extensive overview of current standardization initiatives. All datasets and methods used in the chapters, as well as colour images, are available on www.the-batch-effect-book.org, so that the data can be reproduced. An exciting compilation of state-of-the-art review chapters and latest research results, which will benefit all those involved in the planning, execution, and analysis of gene expression studies.

Statistical Inference for Fractional Diffusion Processes

B. L. S. Prakasa Rao
Statistical Inference for Fractional Diffusion Processes Book PDF

Author : B. L. S. Prakasa Rao
Publisher : John Wiley & Sons
Page : 213 pages
File Size : 51,5 Mb
Release : 2011-07-05
Category : Mathematics
ISBN : 9780470975763

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Statistical Inference for Fractional Diffusion Processes by B. L. S. Prakasa Rao Pdf

Stochastic processes are widely used for model building in the social, physical, engineering and life sciences as well as in financial economics. In model building, statistical inference for stochastic processes is of great importance from both a theoretical and an applications point of view. This book deals with Fractional Diffusion Processes and statistical inference for such stochastic processes. The main focus of the book is to consider parametric and nonparametric inference problems for fractional diffusion processes when a complete path of the process over a finite interval is observable. Key features: Introduces self-similar processes, fractional Brownian motion and stochastic integration with respect to fractional Brownian motion. Provides a comprehensive review of statistical inference for processes driven by fractional Brownian motion for modelling long range dependence. Presents a study of parametric and nonparametric inference problems for the fractional diffusion process. Discusses the fractional Brownian sheet and infinite dimensional fractional Brownian motion. Includes recent results and developments in the area of statistical inference of fractional diffusion processes. Researchers and students working on the statistics of fractional diffusion processes and applied mathematicians and statisticians involved in stochastic process modelling will benefit from this book.

Decision Theory

Giovanni Parmigiani,Lurdes Inoue
Decision Theory Book PDF

Author : Giovanni Parmigiani,Lurdes Inoue
Publisher : John Wiley & Sons
Page : 402 pages
File Size : 43,6 Mb
Release : 2009-04-15
Category : Mathematics
ISBN : 9780470746677

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Decision Theory by Giovanni Parmigiani,Lurdes Inoue Pdf

Decision theory provides a formal framework for making logical choices in the face of uncertainty. Given a set of alternatives, a set of consequences, and a correspondence between those sets, decision theory offers conceptually simple procedures for choice. This book presents an overview of the fundamental concepts and outcomes of rational decision making under uncertainty, highlighting the implications for statistical practice. The authors have developed a series of self contained chapters focusing on bridging the gaps between the different fields that have contributed to rational decision making and presenting ideas in a unified framework and notation while respecting and highlighting the different and sometimes conflicting perspectives. This book: Provides a rich collection of techniques and procedures. Discusses the foundational aspects and modern day practice. Links foundations to practical applications in biostatistics, computer science, engineering and economics. Presents different perspectives and controversies to encourage readers to form their own opinion of decision making and statistics. Decision Theory is fundamental to all scientific disciplines, including biostatistics, computer science, economics and engineering. Anyone interested in the whys and wherefores of statistical science will find much to enjoy in this book.

Multistate Systems Reliability Theory with Applications

Bent Natvig
Multistate Systems Reliability Theory with Applications Book PDF

Author : Bent Natvig
Publisher : John Wiley & Sons
Page : 203 pages
File Size : 53,5 Mb
Release : 2010-12-07
Category : Mathematics
ISBN : 9780470977132

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Multistate Systems Reliability Theory with Applications by Bent Natvig Pdf

Most books in reliability theory are dealing with a description of component and system states as binary: functioning or failed. However, many systems are composed of multi-state components with different performance levels and several failure modes. There is a great need in a series of applications to have a more refined description of these states, for instance, the amount of power generated by an electrical power generation system or the amount of gas that can be delivered through an offshore gas pipeline network. This book provides a descriptive account of various types of multistate system, bound-for multistate systems, probabilistic modeling of monitoring and maintenance of multistate systems with components along with examples of applications. Key Features: Looks at modern multistate reliability theory with applications covering a refined description of components and system states. Presents new research, such as Bayesian assessment of system availabilities and measures of component importance. Complements the methodological description with two substantial case studies. Reliability engineers and students involved in the field of reliability, applied mathematics and probability theory will benefit from this book.

Markov Processes and Applications

Etienne Pardoux
Markov Processes and Applications Book PDF

Author : Etienne Pardoux
Publisher : John Wiley & Sons
Page : 322 pages
File Size : 45,9 Mb
Release : 2008-11-20
Category : Mathematics
ISBN : 9780470721865

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Markov Processes and Applications by Etienne Pardoux Pdf

"This well-written book provides a clear and accessible treatment of the theory of discrete and continuous-time Markov chains, with an emphasis towards applications. The mathematical treatment is precise and rigorous without superfluous details, and the results are immediately illustrated in illuminating examples. This book will be extremely useful to anybody teaching a course on Markov processes." Jean-François Le Gall, Professor at Université de Paris-Orsay, France. Markov processes is the class of stochastic processes whose past and future are conditionally independent, given their present state. They constitute important models in many applied fields. After an introduction to the Monte Carlo method, this book describes discrete time Markov chains, the Poisson process and continuous time Markov chains. It also presents numerous applications including Markov Chain Monte Carlo, Simulated Annealing, Hidden Markov Models, Annotation and Alignment of Genomic sequences, Control and Filtering, Phylogenetic tree reconstruction and Queuing networks. The last chapter is an introduction to stochastic calculus and mathematical finance. Features include: The Monte Carlo method, discrete time Markov chains, the Poisson process and continuous time jump Markov processes. An introduction to diffusion processes, mathematical finance and stochastic calculus. Applications of Markov processes to various fields, ranging from mathematical biology, to financial engineering and computer science. Numerous exercises and problems with solutions to most of them

Nonparametric Statistics

Ricardo Cao,Wenceslao González Manteiga,Juan Romo
Nonparametric Statistics Book PDF

Author : Ricardo Cao,Wenceslao González Manteiga,Juan Romo
Publisher : Springer
Page : 224 pages
File Size : 55,7 Mb
Release : 2016-09-12
Category : Mathematics
ISBN : 9783319415826

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Nonparametric Statistics by Ricardo Cao,Wenceslao González Manteiga,Juan Romo Pdf

This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cádiz (Spain) between June 11–16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid. The 15 articles are a representative sample of the 336 contributed papers presented at the conference. They cover topics such as high-dimensional data modelling, inference for stochastic processes and for dependent data, nonparametric and goodness-of-fit testing, nonparametric curve estimation, object-oriented data analysis, and semiparametric inference. The aim of the ISNPS 2014 conference was to bring together recent advances and trends in several areas of nonparametric statistics in order to facilitate the exchange of research ideas, promote collaboration among researchers from around the globe, and contribute to the further development of the field.

Bayesian Networks

Timo Koski,John Noble
Bayesian Networks Book PDF

Author : Timo Koski,John Noble
Publisher : John Wiley & Sons
Page : 275 pages
File Size : 51,9 Mb
Release : 2011-08-26
Category : Mathematics
ISBN : 9781119964957

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Bayesian Networks by Timo Koski,John Noble Pdf

Bayesian Networks: An Introduction provides a self-contained introduction to the theory and applications of Bayesian networks, a topic of interest and importance for statisticians, computer scientists and those involved in modelling complex data sets. The material has been extensively tested in classroom teaching and assumes a basic knowledge of probability, statistics and mathematics. All notions are carefully explained and feature exercises throughout. Features include: An introduction to Dirichlet Distribution, Exponential Families and their applications. A detailed description of learning algorithms and Conditional Gaussian Distributions using Junction Tree methods. A discussion of Pearl's intervention calculus, with an introduction to the notion of see and do conditioning. All concepts are clearly defined and illustrated with examples and exercises. Solutions are provided online. This book will prove a valuable resource for postgraduate students of statistics, computer engineering, mathematics, data mining, artificial intelligence, and biology. Researchers and users of comparable modelling or statistical techniques such as neural networks will also find this book of interest.

Robust Methods in Biostatistics

Stephane Heritier,Eva Cantoni,Samuel Copt,Maria-Pia Victoria-Feser
Robust Methods in Biostatistics Book PDF

Author : Stephane Heritier,Eva Cantoni,Samuel Copt,Maria-Pia Victoria-Feser
Publisher : John Wiley & Sons
Page : 292 pages
File Size : 43,9 Mb
Release : 2009-05-11
Category : Medical
ISBN : 047074054X

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Robust Methods in Biostatistics by Stephane Heritier,Eva Cantoni,Samuel Copt,Maria-Pia Victoria-Feser Pdf

Robust statistics is an extension of classical statistics that specifically takes into account the concept that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable when the data do not exactly match the postulated models as it is the case for example with outliers. Robust Methods in Biostatistics proposes robust alternatives to common methods used in statistics in general and in biostatistics in particular and illustrates their use on many biomedical datasets. The methods introduced include robust estimation, testing, model selection, model check and diagnostics. They are developed for the following general classes of models: Linear regression Generalized linear models Linear mixed models Marginal longitudinal data models Cox survival analysis model The methods are introduced both at a theoretical and applied level within the framework of each general class of models, with a particular emphasis put on practical data analysis. This book is of particular use for research students,applied statisticians and practitioners in the health field interested in more stable statistical techniques. An accompanying website provides R code for computing all of the methods described, as well as for analyzing all the datasets used in the book.

A Practical Guide to Heavy Tails

Robert Adler,Raya Feldman,Murad Taqqu
A Practical Guide to Heavy Tails Book PDF

Author : Robert Adler,Raya Feldman,Murad Taqqu
Publisher : Springer Science & Business Media
Page : 560 pages
File Size : 42,9 Mb
Release : 1998-10-26
Category : Mathematics
ISBN : 0817639519

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A Practical Guide to Heavy Tails by Robert Adler,Raya Feldman,Murad Taqqu Pdf

Twenty-four contributions, intended for a wide audience from various disciplines, cover a variety of applications of heavy-tailed modeling involving telecommunications, the Web, insurance, and finance. Along with discussion of specific applications are several papers devoted to time series analysis, regression, classical signal/noise detection problems, and the general structure of stable processes, viewed from a modeling standpoint. Emphasis is placed on developments in handling the numerical problems associated with stable distribution (a main technical difficulty until recently). No index. Annotation copyrighted by Book News, Inc., Portland, OR