Описание: This volume of the Selected Papers from Portugal is a product of the Seventeenth Congress of the Portuguese Statistical Society, held at the beautiful resort seaside city of Sesimbra, Portugal, from September 30 to October 3, 2009.
Автор: Gamerman, Dani. Название: Markov Chain Monte Carlo ISBN: 1584885874 ISBN-13(EAN): 9781584885870 Издательство: Taylor&Francis Рейтинг: Цена: 15312.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Incorporating changes in theory and highlighting various applications, this book presents a comprehensive introduction to the methods of Markov Chain Monte Carlo (MCMC) simulation technique. It incorporates the developments in MCMC, including reversible jump, slice sampling, bridge sampling, path sampling, multiple-try, and delayed rejection.
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regression is a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience.
Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat(R) statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R.
By the time you reach the end of the book (and online material) you will have gained:
A clear appreciation of the importance of a statistical approach to the design of your experiments,
A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables,
Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly,
An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working.
The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.
Автор: Pacheco Antonio Название: New Advances in Statistical Modeling and Applications ISBN: 3319053221 ISBN-13(EAN): 9783319053226 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume of the Selected Papers is a product of the XIX Congress of the Portuguese Statistical Society, held at the Portuguese town of Nazare, from September 28 to October 1, 2011. It covers a broad scope of papers in the areas of Statistical Science, Probability and Stochastic Processes, Extremes and Statistical Applications.
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
Описание: This book provides a balanced coverage of underlying theory of statistical analysis of designed experiments and its numerous applications. Data sets from real life studies are used throughout, and graphical as well as formal analyses are illustrated using MINITAB(c) software.
Описание: Statistical Applications for Environmental Analysis and Risk Assessment guides readers through real-world situations and the best statistical methods used to determine the nature and extent of the problem, evaluate the potential human health and ecological risks, and design and implement remedial systems as necessary.
Описание: This book considers specific inferential issues arising from the analysis of dynamic shapes with the attempt to solve the problems at hand using probability models and nonparametric tests.
Автор: Ant?nio Pacheco; Rui Santos; Maria do Ros?rio Oliv Название: New Advances in Statistical Modeling and Applications ISBN: 3319381296 ISBN-13(EAN): 9783319381299 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume of the Selected Papers is a product of the XIX Congress of the Portuguese Statistical Society, held at the Portuguese town of Nazare, from September 28 to October 1, 2011. It covers a broad scope of papers in the areas of Statistical Science, Probability and Stochastic Processes, Extremes and Statistical Applications.
Описание: Today the methods of applied statistics have penetrated very different fields of knowledge, including the investigation oftexts ofvarious origins. These "texts" may be considered as signal sequences of different kinds, long genetic codes, graphic representations (which may be coded and represented by a "text"), as well as actual narrative texts (for example, historical chronicles, originals, documents, etc. ). One ofthe most important problems arising here is to recognize dependent text, i. e., texts which have a measure of "resemblance", arising from some kind of "common origin". For instance, in pattern-recognition problems, it is essential to identify from a large set of "patterns" a pattern that is "closest" to a given one; in studying long signal sequences, it is important to recognize "homogeneous subsequences" and the places of their junction. This includes, in particular, the well-known change-point prob lern, which is given considerable attention in mathematical statistics and the theory of stochastic processes. As applied to the study of narrative texts, the problern of recognizing depen- dent and independent texts ( e . g., chronicles) Ieads to the problern offinding texts having a common source, i. e., the sameoriginal (such texts are naturally called dependent), or, on the contrary, having different sources (such texts are natu- rally called independent). Clearly, such problems are exceedingly complicated, and therefore the appearance of new empirico-statistical recognition methods which, along with the classical approaches, may prove useful in concrete studies (e. g., source determination) is welcome.
Описание: Presents a comprehensive set of mathematical and statistical techniques for the analysis of chronological data. This work concentrates on the development of the mathematical statistical tools and their application to astronomical data, including the Almagest and simulated data (to test the validity of the methods).
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