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The concept of nonparametric smoothing is a central idea in statistics that aims to simultaneously estimate and modes the underlying structure. The book considers high dimensional objects, as density functions and regression. The semiparametric modeling technique compromises the two aims, flexibility and simplicity of statistical procedures, by introducing partial parametric components. These components allow to match structural conditions like e.g. linearity in some variables and may be used to model the influence of discrete variables. The aim of this monograph is to present the statistical and mathematical principles of smoothing with a focus on applicable techniques. The necessary mathematical treatment is easily understandable and a wide variety of interactive smoothing examples are given. The book does naturally split into two parts: Nonparametric models (histogram, kernel density estimation, nonparametric regression) and semiparametric models (generalized regression, single index models, generalized partial linear models, additive and generalized additive models). The first part is intended for undergraduate students majoring in mathematics, statistics, econometrics or biometrics whereas the second part is intended to be used by master and PhD students or researchers. The material is easy to accomplish since the e-book character of the text gives a maximum of flexibility in learning (and teaching) intensity.

Mathematical statistics --- Nonparametric statistics --- Probabilities. --- Statistics . --- Econometrics. --- Probability Theory and Stochastic Processes. --- Statistics for Business, Management, Economics, Finance, Insurance. --- Statistical Theory and Methods. --- Economics, Mathematical --- Statistics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Risk

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Biostatistics is one of the scientific fields for which the recent developments have been extremely important. It is also strongly related to other scientific disciplines involving statistical methodology. The aim of this book is to cover a wide scope of recent statistical methods used by scientists in biostatistics as well as in other related fields such as chemometrics, environmetrics and geophysics. The contributed papers, coming from internationally recognized researchers, present various statistical methodologies together with a selected scope of their main mathematical properties and their applications in real case studies, making this book of interest to a wide audience among researchers and students in statistics. Each method is accompanied with interactive and automatic Xplore routines, available on-line, allowing people to reproduce the proposed examples or to apply the methods to their own real datasets. Thus this book will also be of special interest to practitioners.

Statistical science --- Statistical physics --- Biomathematics. Biometry. Biostatistics --- Engineering sciences. Technology --- medische statistiek --- statistische kwaliteitscontrole --- industriële statistieken --- biostatistiek --- biometrie --- statistisch onderzoek

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Most of the observable phenomena in the empirical sciences are of a multivariate nature.  In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices.  In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication.  In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior.  The underlying data structure of these and many other quantitative studies of applied sciences is multivariate.  Focusing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data.  The book surveys the basic principles of multivariate statistical data analysis and emphasizes both exploratory and inferential statistics.  All chapters have exercises that highlight applications in different fields. The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features A new Chapter on Regression Models has been added All numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.

Statistical science --- Quantitative methods (economics) --- Economic schools --- Mathematical statistics --- Financial analysis --- Business economics --- statistiek --- economisch denken --- financiële analyse --- econometrie --- statistisch onderzoek

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Statistical Tools in Finance and Insurance presents ready-to-use solutions, theoretical developments and method construction for many practical problems in quantitative finance and insurance. Written by practitioners and leading academics in the field of quantitative finance and insurance, this book offers a unique combination of topics from which every market analyst and risk manager will benefit. Features of the book: - Offers insight into new methods and the applicability of the stochastic technology - Provides the tools, instruments and (online) algorithms for recent techniques in quantitative finance and modern treatments in insurance calculations. - Covers topics such as heavy tailed distributions, implied trinomial trees, pricing of CAT bonds, simulation of risk processes and ruin probability approximation - Presents extensive examples - The downloadable electronic edition of the book offers interactive tools "This book presents modern tools for quantitative analysis in finance and insurance. It provides a smooth introduction into advanced techniques applicable to a wide range of practical problems. The fact that all examples can be reproduced by the XploRe Quantlet Server technique makes it a "sure buy" for both practioners and theoretical analysts." Prof. Dr. Helmut Gründl, Dr. Wolfgang Schieren Chair for Insurance and Risk Management, sponsored by Allianz AG and Stifterverband für die Deutsche Wissenschaft  

Quantitative methods (economics) --- Mathematical statistics --- Financial analysis --- Business economics --- statistiek --- verzekeringen --- financiële analyse --- econometrie

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Antony Unwin, Chun-houh Chen, Wolfgang K. Härdle 1. 1 Computational Statistics and Data Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Data Visualization and Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Presentation and Exploratory Graphics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Graphics and Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 1. 2 The Chapters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Summary and Overview; Part II. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Summary and Overview; Part III. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Summary and Overview; Part IV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 The Authors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 1. 3 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4 Antony Unwin, Chun-houh Chen, Wolfgang K. Härdle Computational Statistics 1. 1 and Data Visualization Tis book is the third volume of the Handbook of Computational Statistics and c- ers the ?eld of data visualization. In line with the companion volumes, it contains a collection of chapters by experts in the ?eld to present readers with an up-to-date and comprehensive overview of the state of the art. Data visualization is an active area of application and research, and this is a good time to gather together a summary of current knowledge. Graphic displays are ofen very e?ective at communicating information. Tey are also very ofen not e?ective at communicating information. Two important reasons for this state of a?airs are that graphics can be produced with a few clicks of the mouse without any thought and the design of graphics is not taken seriously in many scienti?c textbooks.

Statistical science --- Molecular biology --- Programming --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- grafische vormgeving --- informatica --- statistiek --- KI (kunstmatige intelligentie) --- moleculaire biologie --- statistisch onderzoek