an introduction to the bootstrap monographs on statistics and applied probability

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An Introduction To The Bootstrap

Author : Bradley Efron
ISBN : 0412042312
Genre : Mathematics
File Size : 54. 10 MB
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Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.

Gewu T Wie Praxisleitfaden Seriation Und Korrespondenzanalyse In Der Arch Ologie

Author : Frank Siegmund
ISBN : 9783739298016
Genre : History
File Size : 58. 2 MB
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Seriation und Korrespondenzanalyse (CA) sind statistische Verfahren, die in der Archäologie häufig angewendet werden. Die CA dient vor allem dazu, die Kombination von Objekten (Typen) in zahlreichen Fundkomplexen wie z. B. Gräbern, Horten oder Siedlungsgruben zu analysieren, um deren relative zeitliche Abfolge aufzudecken. Das Buch führt in die Methode ein und bietet vor allem auf Basis der freien Software PAST eine praktische Einführung mit konkreten Übungsbeispielen. Der Text ist zum Selbststudium gedacht. Nach Durcharbeiten des Leitfadens und der Übungen ist der Leser in der Lage, selbständig eigene Analysen durchzuführen und auszuwerten. Der Praxisleitfaden ist von einem Archäologen für Archäologen geschrieben und mit Studierenden der Archäologie getestet, doch die Methode ist auch für andere Wissensbereiche wie etwa die Sozialwissenschaften oder Biologie und Ökologie relevant. Grundlage der praktischen Übungen ist die freie Software PAST, die für Rechner unter MS-Windows sowie MACs verfügbar ist.

Das Mobiltelefon Im Spiegel Fiktionaler Fernsehserien

Author : Veronika Karnowski
ISBN : 9783531912110
Genre : Social Science
File Size : 49. 63 MB
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Probability And Statistics With R

Author : Maria Dolores Ugarte
ISBN : 9781584888925
Genre : Mathematics
File Size : 84. 58 MB
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Designed for an intermediate undergraduate course, Probability and Statistics with R shows students how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs to facilitate hands-on learning. Integrating theory with practice, the text briefly introduces the syntax, structures, and functions of the S language, before covering important graphically and numerically descriptive methods. The next several chapters elucidate probability and random variables topics, including univariate and multivariate distributions. After exploring sampling distributions, the authors discuss point estimation, confidence intervals, hypothesis testing, and a wide range of nonparametric methods. With a focus on experimental design, the book also presents fixed- and random-effects models as well as randomized block and two-factor factorial designs. The final chapter describes simple and multiple regression analyses. Demonstrating that R can be used as a powerful teaching aid, this comprehensive text presents extensive treatments of data analysis using parametric and nonparametric techniques. It effectively links statistical concepts with R procedures, enabling the application of the language to the vast world of statistics.

Self Normalized Processes

Author : Victor H. Peña
ISBN : 9783540856368
Genre : Mathematics
File Size : 67. 10 MB
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Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference. The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization.

Copulae And Multivariate Probability Distributions In Finance

Author : Alexandra Dias
ISBN : 9781317976905
Genre : Business & Economics
File Size : 60. 66 MB
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Portfolio theory and much of asset pricing, as well as many empirical applications, depend on the use of multivariate probability distributions to describe asset returns. Traditionally, this has meant the multivariate normal (or Gaussian) distribution. More recently, theoretical and empirical work in financial economics has employed the multivariate Student (and other) distributions which are members of the elliptically symmetric class. There is also a growing body of work which is based on skew-elliptical distributions. These probability models all exhibit the property that the marginal distributions differ only by location and scale parameters or are restrictive in other respects. Very often, such models are not supported by the empirical evidence that the marginal distributions of asset returns can differ markedly. Copula theory is a branch of statistics which provides powerful methods to overcome these shortcomings. This book provides a synthesis of the latest research in the area of copulae as applied to finance and related subjects such as insurance. Multivariate non-Gaussian dependence is a fact of life for many problems in financial econometrics. This book describes the state of the art in tools required to deal with these observed features of financial data. This book was originally published as a special issue of the European Journal of Finance.

Methods Matter

Author : Richard J. Murnane
ISBN : 9780199890156
Genre : Psychology
File Size : 88. 72 MB
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Educational policy-makers around the world constantly make decisions about how to use scarce resources to improve the education of children. Unfortunately, their decisions are rarely informed by evidence on the consequences of these initiatives in other settings. Nor are decisions typically accompanied by well-formulated plans to evaluate their causal impacts. As a result, knowledge about what works in different situations has been very slow to accumulate. Over the last several decades, advances in research methodology, administrative record keeping, and statistical software have dramatically increased the potential for researchers to conduct compelling evaluations of the causal impacts of educational interventions, and the number of well-designed studies is growing. Written in clear, concise prose, Methods Matter: Improving Causal Inference in Educational and Social Science Research offers essential guidance for those who evaluate educational policies. Using numerous examples of high-quality studies that have evaluated the causal impacts of important educational interventions, the authors go beyond the simple presentation of new analytical methods to discuss the controversies surrounding each study, and provide heuristic explanations that are also broadly accessible. Murnane and Willett offer strong methodological insights on causal inference, while also examining the consequences of a wide variety of educational policies implemented in the U.S. and abroad. Representing a unique contribution to the literature surrounding educational research, this landmark text will be invaluable for students and researchers in education and public policy, as well as those interested in social science.

Wahrscheinlichkeitsrechnung Und Statistik

Author : Robert Hafner
ISBN : 9783709169445
Genre : Mathematics
File Size : 85. 58 MB
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Das Buch ist eine Einführung in die Wahrscheinlichkeitsrechnung und mathematische Statistik auf mittlerem mathematischen Niveau. Die Pädagogik der Darstellung unterscheidet sich in wesentlichen Teilen – Einführung der Modelle für unabhängige und abhängige Experimente, Darstellung des Suffizienzbegriffes, Ausführung des Zusammenhanges zwischen Testtheorie und Theorie der Bereichschätzung, allgemeine Diskussion der Modellentwicklung – erheblich von der anderer vergleichbarer Lehrbücher. Die Darstellung ist, soweit auf diesem Niveau möglich, mathematisch exakt, verzichtet aber bewußt und ebenfalls im Gegensatz zu vergleichbaren Texten auf die Erörterung von Meßbarkeitsfragen. Der Leser wird dadurch erheblich entlastet, ohne daß wesentliche Substanz verlorengeht. Das Buch will allen, die an der Anwendung der Statistik auf solider Grundlage interessiert sind, eine Einführung bieten, und richtet sich an Studierende und Dozenten aller Studienrichtungen, für die mathematische Statistik ein Werkzeug ist.

Einf Hrung In Die Statistik Der Finanzm Rkte

Author : Jürgen Franke
ISBN : 9783642170492
Genre : Business & Economics
File Size : 90. 38 MB
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Density Estimation For Statistics And Data Analysis

Author : Bernard. W. Silverman
ISBN : 0412246201
Genre : Mathematics
File Size : 38. 22 MB
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Although there has been a surge of interest in density estimation in recent years, much of the published research has been concerned with purely technical matters with insufficient emphasis given to the technique's practical value. Furthermore, the subject has been rather inaccessible to the general statistician. The account presented in this book places emphasis on topics of methodological importance, in the hope that this will facilitate broader practical application of density estimation and also encourage research into relevant theoretical work. The book also provides an introduction to the subject for those with general interests in statistics. The important role of density estimation as a graphical technique is reflected by the inclusion of more than 50 graphs and figures throughout the text. Several contexts in which density estimation can be used are discussed, including the exploration and presentation of data, nonparametric discriminant analysis, cluster analysis, simulation and the bootstrap, bump hunting, projection pursuit, and the estimation of hazard rates and other quantities that depend on the density. This book includes general survey of methods available for density estimation. The Kernel method, both for univariate and multivariate data, is discussed in detail, with particular emphasis on ways of deciding how much to smooth and on computation aspects. Attention is also given to adaptive methods, which smooth to a greater degree in the tails of the distribution, and to methods based on the idea of penalized likelihood.

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