Menu Close

An Introduction To Statistical Modeling Of Extreme Values

These are the books for those you who looking for to read the An Introduction To Statistical Modeling Of Extreme Values, try to read or download Pdf/ePub books and some of authors may have disable the live reading. Check the book if it available for your country and user who already subscribe will have full access all free books from the library source.

An Introduction to Statistical Modeling of Extreme Values

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Statistical Modeling of Extreme Values by Stuart Coles Book Summary:

Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.

An Introduction to Statistical Modeling of Extreme Values

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Statistical Modeling of Extreme Values by Stuart Coles Book Summary:

Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.

An Introduction to Statistical Modeling of Extreme Values

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Statistical Modeling of Extreme Values by Stuart Coles Book Summary:

Download or read An Introduction to Statistical Modeling of Extreme Values book by clicking button below to visit the book download website. There are multiple format available for you to choose (Pdf, ePub, Doc).

Statistical Analysis of Extreme Values

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Statistical Analysis of Extreme Values by Rolf-Dieter Reiss,Michael Thomas Book Summary:

Statistical analysis of extreme data is vital to many disciplines including hydrology, insurance, finance, engineering and environmental sciences. This book provides a self-contained introduction to parametric modeling, exploratory analysis and statistical interference for extreme values. For this Third Edition, the entire text has been thoroughly updated and rearranged to meet contemporary requirements, with new sections and chapters address such topics as dependencies, the conditional analysis and the multivariate modeling of extreme data. New chapters include An Overview of Reduced-Bias Estimation; The Spectral Decomposition Methodology; About Tail Independence; and Extreme Value Statistics of Dependent Random Variables.

Extreme Value Theory

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Extreme Value Theory by Laurens de Haan,Ana Ferreira Book Summary:

Focuses on theoretical results along with applications All the main topics covering the heart of the subject are introduced to the reader in a systematic fashion Concentration is on the probabilistic and statistical aspects of extreme values Excellent introduction to extreme value theory at the graduate level, requiring only some mathematical maturity

Extreme Value Theory in Engineering

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Extreme Value Theory in Engineering by Enrique Castillo Book Summary:

This book is a comprehensive guide to extreme value theory in engineering. Written for the end user with intermediate and advanced statistical knowledge, it covers classical methods as well as recent advances. A collection of 150 examples illustrates the theoretical results and takes the reader from simple applications through complex cases of dependence.

Statistics II for Dummies

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Statistics II for Dummies by Deborah J. Rumsey Book Summary:

The ideal supplement and study guide for students preparing for advanced statistics Packed with fresh and practical examples appropriate for a range of degree-seeking students, Statistics II For Dummies helps any reader succeed in an upper-level statistics course. It picks up with data analysis where Statistics For Dummies left off, featuring new and updated examples, real-world applications, and test-taking strategies for success. This easy-to-understand guide covers such key topics as sorting and testing models, using regression to make predictions, performing variance analysis (ANOVA), drawing test conclusions with chi-squares, and making comparisons with the Rank Sum Test.

Extreme Values, Regular Variation and Point Processes

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Extreme Values, Regular Variation and Point Processes by Sidney I. Resnick Book Summary:

This book examines the fundamental mathematical and stochastic process techniques needed to study the behavior of extreme values of phenomena based on independent and identically distributed random variables and vectors. It emphasizes the core primacy of three topics necessary for understanding extremes: the analytical theory of regularly varying functions; the probabilistic theory of point processes and random measures; and the link to asymptotic distribution approximations provided by the theory of weak convergence of probability measures in metric spaces.

An Introduction to Statistical Learning

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Statistical Learning by Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani Book Summary:

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Extreme Value Modeling and Risk Analysis

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Extreme Value Modeling and Risk Analysis by Taylor & Francis Group Book Summary:

Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subject. After reviewing univariate extreme value analysis and multivariate extremes, the book explains univariate extreme value mixture modeling, threshold selection in extreme value analysis, and threshold modeling of non-stationary extremes. It presents new results for block-maxima of vine copulas, develops time series of extremes with applications from climatology, describes max-autoregressive and moving maxima models for extremes, and discusses spatial extremes and max-stable processes. The book then covers simulation and conditional simulation of max-stable processes; inference methodologies, such as composite likelihood, Bayesian inference, and approximate Bayesian computation; and inferences about extreme quantiles and extreme dependence. It also explores novel applications of extreme value modeling, including financial investments, insurance and financial risk management, weather and climate disasters, clinical trials, and sports statistics. Risk analyses related to extreme events require the combined expertise of statisticians and domain experts in climatology, hydrology, finance, insurance, sports, and other fields. This book connects statistical/mathematical research with critical decision and risk assessment/management applications to stimulate more collaboration between these statisticians and specialists.

Copula Theory and Its Applications

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Copula Theory and Its Applications by Piotr Jaworski,Fabrizio Durante,Wolfgang Karl Härdle,Tomasz Rychlik Book Summary:

Copulas are mathematical objects that fully capture the dependence structure among random variables and hence offer great flexibility in building multivariate stochastic models. Since their introduction in the early 50's, copulas have gained considerable popularity in several fields of applied mathematics, such as finance, insurance and reliability theory. Today, they represent a well-recognized tool for market and credit models, aggregation of risks, portfolio selection, etc. This book is divided into two main parts: Part I - "Surveys" contains 11 chapters that provide an up-to-date account of essential aspects of copula models. Part II - "Contributions" collects the extended versions of 6 talks selected from papers presented at the workshop in Warsaw.

Heavy-Tail Phenomena

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Heavy-Tail Phenomena by Sidney I. Resnick Book Summary:

This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. Heavy tails are characteristic of phenomena where there is a significant probability of a single huge value impacting system behavior. Record-breaking insurance losses, financial returns, sizes of files stored on a server and transmission rates of files are all examples of heavy-tailed phenomena. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use (or at least to learn) a statistics package such as R or Splus.

Introduction to Statistical Modelling

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Introduction to Statistical Modelling by Annette J. Dobson Book Summary:

This book is about generalized linear models as described by NeIder and Wedderburn (1972). This approach provides a unified theoretical and computational framework for the most commonly used statistical methods: regression, analysis of variance and covariance, logistic regression, log-linear models for contingency tables and several more specialized techniques. More advanced expositions of the subject are given by McCullagh and NeIder (1983) and Andersen (1980). The emphasis is on the use of statistical models to investigate substantive questions rather than to produce mathematical descriptions of the data. Therefore parameter estimation and hypothesis testing are stressed. I have assumed that the reader is familiar with the most commonly used statistical concepts and methods and has some basic knowledge of calculus and matrix algebra. Short numerical examples are used to illustrate the main points. In writing this book I have been helped greatly by the comments and criticism of my students and colleagues, especially Anne Young. However, the choice of material, and the obscurities and errors are my responsibility and I apologize to the reader for any irritation caused by them. For typing the manuscript under difficult conditions I am grateful to Anne McKim, Jan Garnsey, Cath Claydon and Julie Latimer.

Forecasting and Assessing Risk of Individual Electricity Peaks

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Forecasting and Assessing Risk of Individual Electricity Peaks by Maria Jacob,Cláudia Neves,Danica Vukadinović Greetham Book Summary:

The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples. In order to achieve carbon targets, good forecasts of peaks are essential. For instance, shifting demand or charging battery depends on correct demand predictions in time. Majority of forecasting algorithms historically were focused on average load prediction. In order to model the peaks, methods from extreme value theory are applied. This allows us to study extremes without making any assumption on the central parts of demand distribution and to predict beyond the range of available data. While applied on individual loads, the techniques described in this book can be extended naturally to substations, or to commercial settings. Extreme value theory techniques presented can be also used across other disciplines, for example for predicting heavy rainfalls, wind speed, solar radiation and extreme weather events. The book is intended for students, academics, engineers and professionals that are interested in short term load prediction, energy data analytics, battery control, demand side response and data science in general.

Applied Statistical Methods

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Applied Statistical Methods by Irving W. Burr Book Summary:

Applied Statistical Methods covers the fundamental understanding of statistical methods necessary to deal with a wide variety of practical problems. This 14-chapter text presents the topics covered in a manner that stresses clarity of understanding, interpretation, and method of application. The introductory chapter illustrates the importance of statistical analysis. The next chapters introduce the methods of data summarization, including frequency distributions, cumulative frequency distributions, and measures of central tendency and variability. These topics are followed by discussions of the fundamental principles of probability, the concepts of sample spaces, outcomes, events, probability, independence of events, and the characterization of discrete and continuous random variables. Other chapters explore the distribution of several important statistics; statistical tests of hypotheses; point and interval estimation; and simple linear regression. The concluding chapters review the elements of single- and two-factor analysis of variance and the design of analysis of variance experiments. This book is intended primarily for advanced undergraduate and graduate students in the mathematical, physical, and engineering sciences, as well as in economics, business, and related areas. Researchers and line personnel in industry and government will find this book useful in self-study.

Economic Time Series

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Economic Time Series by William R. Bell,Scott H. Holan,Tucker S. McElroy Book Summary:

Economic Time Series: Modeling and Seasonality is a focused resource on analysis of economic time series as pertains to modeling and seasonality, presenting cutting-edge research that would otherwise be scattered throughout diverse peer-reviewed journals. This compilation of 21 chapters showcases the cross-fertilization between the fields of time series modeling and seasonal adjustment, as is reflected both in the contents of the chapters and in their authorship, with contributors coming from academia and government statistical agencies. For easier perusal and absorption, the contents have been grouped into seven topical sections: Section I deals with periodic modeling of time series, introducing, applying, and comparing various seasonally periodic models Section II examines the estimation of time series components when models for series are misspecified in some sense, and the broader implications this has for seasonal adjustment and business cycle estimation Section III examines the quantification of error in X-11 seasonal adjustments, with comparisons to error in model-based seasonal adjustments Section IV discusses some practical problems that arise in seasonal adjustment: developing asymmetric trend-cycle filters, dealing with both temporal and contemporaneous benchmark constraints, detecting trading-day effects in monthly and quarterly time series, and using diagnostics in conjunction with model-based seasonal adjustment Section V explores outlier detection and the modeling of time series containing extreme values, developing new procedures and extending previous work Section VI examines some alternative models and inference procedures for analysis of seasonal economic time series Section VII deals with aspects of modeling, estimation, and forecasting for nonseasonal economic time series By presenting new methodological developments as well as pertinent empirical analyses and reviews of established methods, the book provides much that is stimulating and practically useful for the serious researcher and analyst of economic time series.

Climate and Social Stress

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Climate and Social Stress by National Research Council,Division of Behavioral and Social Sciences and Education,Board on Environmental Change and Society,Committee on Assessing the Impacts of Climate Change on Social and Political Stresses Book Summary:

Climate change can reasonably be expected to increase the frequency and intensity of a variety of potentially disruptive environmental events--slowly at first, but then more quickly. It is prudent to expect to be surprised by the way in which these events may cascade, or have far-reaching effects. During the coming decade, certain climate-related events will produce consequences that exceed the capacity of the affected societies or global systems to manage; these may have global security implications. Although focused on events outside the United States, Climate and Social Stress: Implications for Security Analysis recommends a range of research and policy actions to create a whole-of-government approach to increasing understanding of complex and contingent connections between climate and security, and to inform choices about adapting to and reducing vulnerability to climate change.

The Economics of Forest Disturbances

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

The Economics of Forest Disturbances by Thomas P. Holmes,Jeffrey P. Prestemon,Karen L. Abt Book Summary:

by Peter J. Roussopoulos, Director, Southern Research Station The world and its ecosystems are repeatedly punctuated by natural disturbances, and human societies must learn to manage this reality Often severe and unp- dictable, dynamic natural forces disrupt human welfare and alter the structure and composition of natural systems Over the past century, land management ag- cies within the United States have relied on science to improve the sustainable management of natural resources Forest economics research can help advance this scientifc basis by integrating knowledge of forest disturbance processes with their economic causes and consequences As the twenty-frst century unfolds, people increasingly seek the goods and services provided by forest ecosystems, not only for wood supply, clean water, and leisure pursuits, but also to establish residential communities that are removed from the hustle and bustle of urban life As vividly demonstrated during the past few years, Santa Ana winds can blow wildfres down from the mountains of California, incinerating homes as readily as vegetation in the canyons below Hurricanes can fatten large swaths of forest land, while associated foods create havoc for urban and rural residents alike Less dramatic, but more insidious, trees and forest stands are succumbing to exotic insects and diseases, causing economic losses to private property values (including timber) as well as scenic and recreation values As human demands on public and private forests expand, science-based solutions need to be identifed so that social needs can be balanced with the vagaries of forest disturbance processes

Attribution of Extreme Weather Events in the Context of Climate Change

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Attribution of Extreme Weather Events in the Context of Climate Change by National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Atmospheric Sciences and Climate,Committee on Extreme Weather Events and Climate Change Attribution Book Summary:

As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.

Handbook of Statistical Analysis and Data Mining Applications

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Handbook of Statistical Analysis and Data Mining Applications by Robert Nisbet,Gary Miner,Ken Yale Book Summary:

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Statistics of Extremes

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Statistics of Extremes by Jan Beirlant,Yuri Goegebeur,Johan Segers,Jozef L. Teugels Book Summary:

Research in the statistical analysis of extreme values has flourished over the past decade: new probability models, inference and data analysis techniques have been introduced; and new application areas have been explored. Statistics of Extremes comprehensively covers a wide range of models and application areas, including risk and insurance: a major area of interest and relevance to extreme value theory. Case studies are introduced providing a good balance of theory and application of each model discussed, incorporating many illustrated examples and plots of data. The last part of the book covers some interesting advanced topics, including time series, regression, multivariate and Bayesian modelling of extremes, the use of which has huge potential.

Clinical Prediction Models

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Clinical Prediction Models by Ewout W. Steyerberg Book Summary:

Prediction models are important in various fields, including medicine, physics, meteorology, and finance. Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics. Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment. The current era of evidence-based medicine asks for an individualized approach to medical decision-making. Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individu- ized predictions of a diagnostic or prognostic outcome. Why Read This Book? My motivation for working on this book stems primarily from the fact that the development and applications of prediction models are often suboptimal in medical publications. With this book I hope to contribute to better understanding of relevant issues and give practical advice on better modelling strategies than are nowadays widely used. Issues include: (a) Better predictive modelling is sometimes easily possible; e.g. a large data set with high quality data is available, but all continuous predictors are dich- omized, which is known to have several disadvantages.

Statistical Techniques for Modelling Extreme Value Data and Related Applications

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Statistical Techniques for Modelling Extreme Value Data and Related Applications by Haroon M. Barakat,El-Sayed M. Nigm,Osama M. Khaled Book Summary:

This book tackles some modern trends and methods in the modelling of extreme data. Usually such data arise from random phenomena such as floods, hurricanes, air and water pollutants, extreme claim sizes, life spans, and maximum sizes of ecological populations. It provides the latest statistical methods to model these random phenomena to understand and predict them, thus allowing the avoidance of damage or at least minimizing it. In addition, this book sheds light on the mathematical and statistical theories on which applied modelling methods were built. Therefore, it has both an applied and theoretical orientation, and represents a valuable addition to existing literature on the modelling of extreme value data.

Dependence Modeling with Copulas

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Dependence Modeling with Copulas by Harry Joe Book Summary:

Dependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.

An Introduction to Stochastic Modeling

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Stochastic Modeling by Howard M. Taylor,Samuel Karlin Book Summary:

Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Third Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems. Realistic applications from a variety of disciplines integrated throughout the text Plentiful, updated and more rigorous problems, including computer "challenges" Revised end-of-chapter exercises sets-in all, 250 exercises with answers New chapter on Brownian motion and related processes Additional sections on Matingales and Poisson process

Heavy-Tailed Time Series

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Heavy-Tailed Time Series by Rafal Kulik,Philippe Soulier Book Summary:

This book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology. Appropriate for graduate coursework or professional reference, the book requires a background in extreme value theory for i.i.d. data and basics of time series. Following a brief review of foundational concepts, it progresses linearly through topics in limit theorems and time series models while including historical insights at each chapter’s conclusion. Additionally, the book incorporates complete proofs and exercises with solutions as well as substantive reference lists and appendices, featuring a novel commentary on the theory of vague convergence.

Probability and Statistical Models

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Probability and Statistical Models by Arjun K. Gupta,Wei-Bin Zeng,Yanhong Wu Book Summary:

With an emphasis on models and techniques, this textbook introduces many of the fundamental concepts of stochastic modeling that are now a vital component of almost every scientific investigation. In particular, emphasis is placed on laying the foundation for solving problems in reliability, insurance, finance, and credit risk. The material has been carefully selected to cover the basic concepts and techniques on each topic, making this an ideal introductory gateway to more advanced learning. With exercises and solutions to selected problems accompanying each chapter, this textbook is for a wide audience including advanced undergraduate and beginning-level graduate students, researchers, and practitioners in mathematics, statistics, engineering, and economics.

Spanish Alphabet Coloring Book

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Spanish Alphabet Coloring Book by Nina Barbaresi Book Summary:

Illustrating over 150 basic words in the Spanish language, from arbol (tree) to zapatos (shoes). The Spanish word appears next to each image, and again at the bottom of the page with its definite article and English translation.

Economic Models of Tropical Deforestation: A Review

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Economic Models of Tropical Deforestation: A Review by David Kaimowitz,Arild Angelsen Book Summary:

Types of economic deforestation models. Household and firm-level models. Regional-level models. National and macro-level models. Priority areas for future research.

Competing Risks and Multistate Models with R

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Competing Risks and Multistate Models with R by Jan Beyersmann,Arthur Allignol,Martin Schumacher Book Summary:

This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.

The Elements of Statistical Learning

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

The Elements of Statistical Learning by Trevor Hastie,Robert Tibshirani,Jerome Friedman Book Summary:

During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

Heavy-Tail Phenomena

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Heavy-Tail Phenomena by Sidney I. Resnick Book Summary:

This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. It is uniquely devoted to heavy-tails and emphasizes both probability modeling and statistical methods for fitting models. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use a statistics package. This work will serve second-year graduate students and researchers in the areas of applied mathematics, statistics, operations research, electrical engineering, and economics.

Experimental Design and Data Analysis for Biologists

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Experimental Design and Data Analysis for Biologists by Jerry P. Queen,Gerry P. Quinn,Michael J. Keough Book Summary:

An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.

Modelling Extremal Events

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Modelling Extremal Events by Paul Embrechts,Claudia Klüppelberg,Thomas Mikosch Book Summary:

"A reader's first impression on leafing through this book is of the large number of graphs and diagrams, used to illustrate shapes of distributions...and to show real data examples in various ways. A closer reading reveals a nice mix of theory and applications, with the copious graphical illustrations alluded to. Such a mixture is of course dear to the heart of the applied probabilist/statistician, and should impress even the most ardent theorists." --MATHEMATICAL REVIEWS

Test Equating, Scaling, and Linking

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Test Equating, Scaling, and Linking by Michael J. Kolen,Robert L. Brennan Book Summary:

This book provides an introduction to test equating, scaling and linking, including those concepts and practical issues that are critical for developers and all other testing professionals. In addition to statistical procedures, successful equating, scaling and linking involves many aspects of testing, including procedures to develop tests, to administer and score tests and to interpret scores earned on tests. Test equating methods are used with many standardized tests in education and psychology to ensure that scores from multiple test forms can be used interchangeably. Test scaling is the process of developing score scales that are used when scores on standardized tests are reported. In test linking, scores from two or more tests are related to one another. Linking has received much recent attention, due largely to investigations of linking similarly named tests from different test publishers or tests constructed for different purposes. In recent years, researchers from the education, psychology and statistics communities have contributed to the rapidly growing statistical and psychometric methodologies used in test equating, scaling and linking. In addition to the literature covered in previous editions, this new edition presents coverage of significant recent research. In order to assist researchers, advanced graduate students and testing professionals, examples are used frequently and conceptual issues are stressed. New material includes model determination in log-linear smoothing, in-depth presentation of chained linear and equipercentile equating, equating criteria, test scoring and a new section on scores for mixed-format tests. In the third edition, each chapter contains a reference list, rather than having a single reference list at the end of the volume The themes of the third edition include: * the purposes of equating, scaling and linking and their practical context * data collection designs * statistical methodology * designing reasonable and useful equating, scaling, and linking studies * importance of test development and quality control processes to equating * equating error, and the underlying statistical assumptions for equating

An Introduction to Mathematical Modeling

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Mathematical Modeling by Edward A. Bender Book Summary:

Accessible text features over 100 reality-based examples pulled from the science, engineering, and operations research fields. Prerequisites: ordinary differential equations, continuous probability. Numerous references. Includes 27 black-and-white figures. 1978 edition.

Stated Choice Methods

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Stated Choice Methods by Jordan J. Louviere,David A. Hensher,Joffre D. Swait Book Summary:

Multidisciplinary graduate and practitioner guide offering the theory and application of stated choice methods.

Discrete Choice Methods with Simulation

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Discrete Choice Methods with Simulation by Kenneth Train Book Summary:

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

An Introduction to Mathematical Statistics

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

An Introduction to Mathematical Statistics by Fetsje Bijma Book Summary:

Statistics is the science that focuses on drawing conclusions from data, by modeling and analyzing the data using probabilistic models. In An Introduction to Mathematical Statistics, the authors describe key concepts from statistics and give a mathematical basis for important statistical methods. Much attention is paid to the sound application of those methods to data. The three main topics in statistics are estimators, tests, and confidence regions. The authors illustrate these in many examples, with a separate chapter on regression models, including linear regression and analysis of variance. They also discuss the optimality of estimators and tests, as well as the selection of the best-fitting model. Each chapter ends with a case study in which the described statistical methods are applied. This book assumes a basic knowledge of probability theory, calculus, and linear algebra.

Statistics of Extremes

An Introduction To Statistical Modeling Of Extreme Values [Pdf/ePub] eBook

Statistics of Extremes by E. J. Gumbel Book Summary:

Indisputably recognized as a classic in its field, Statistics of Extremes was the first book to exclusively evaluate the relevance of maximum and minimum (extreme) values. More than fifty years after publication, it remains relevant and helpful to the contemporary work of statisticians, engineers, and scientists. In this far-sighted and important work, Gumbel explains the applications of statistical extremes and reinforces its main ideas with generalized exercises. Key topics in this book include: Aims and tools Order statistics and their exceedances Exact distribution of extremes Analytical study of extremes First asymptotic distribution Uses of the first, second, and third asymptotes Range To remain relevant to a wide audience of statisticians, Professor Gumbel relies on elementary language to convey highly technical concepts. With 47 tables and 97 graphs, the focus is on graphical procedures rather than calculations. Gumbel's original research in the 1940s was developed to predict natural disasters, but as he further refined his theory and tools of extreme statistics, it became clear it has applications in numerous fields.