Download or read book Proceedings of the X International Summer Conference on Probability and Statistics and Seminar on Statistical Data Analysis SDA 2003 written by International Summer Conference on Probability and Statistics. 10, 2003, Sozopol and published by . This book was released on 2004 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the X International Summer Conference on Probability and Statistics and Seminar on Statistical Data Analysis SDA 2003 written by 2003 International Summer Conference on Probability and Statistics 10, Sozopol and published by . This book was released on 2004 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the XI International Summer Conference on Probability and Statistics and Seminar on Statistical Data Analysis SDA 2004 written by International Summer Conference on Probability and Statistics and published by . This book was released on 2005 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the XII International Summer Conference on Probability and Statistics and Seminar on Statistical Data Analysis SDA 2006 written by International Summer Conference on Probability and Statistics and published by . This book was released on 2007 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the XV International Summer Conference on Probability and Statistics Seminar on Statistical Data Analysis SDA 2012 Workshop on Branching Processes and Applications written by Nikolaj M. Janev and published by . This book was released on 2013 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the XIV International Summer Conference on Probability and Statistics Seminar on Statistical Data Analysis SDA 2010 Workshop on Branching Processes written by Nikolaj M. Janev and published by . This book was released on 2011 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the XVI th International Summer Conference on Probability and Statistics Seminar on Statistical Data Analysis Workshop on Branching Processes and Applications 21 29 June 2014 Pomorie Bulgaria written by and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Pliska written by and published by . This book was released on 2004 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the Berkeley Symposium on Mathematical Statistics and Probability written by Jerzy Neyman and published by Univ of California Press. This book was released on 1949 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Teaching of Probability Statistics written by Lennart Råde and published by . This book was released on 1970 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Statistical Sciences and Data Analysis written by Kameo Matusita and published by de Gruyter. This book was released on 1993 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings of the 2 Berkeley Symposium on Mathematical Statistics and Probability written by Berkeley Symposium on Mathematical Statistics and Probability. 2, 1950 and published by . This book was released on 1951 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Introduction to Categorical Data Analysis written by Alan Agresti and published by John Wiley & Sons. This book was released on 2018-10-11 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable new edition of a standard reference The use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An Introduction to Categorical Data Analysis, Third Edition summarizes these methods and shows readers how to use them using software. Readers will find a unified generalized linear models approach that connects logistic regression and loglinear models for discrete data with normal regression for continuous data. Adding to the value in the new edition is: • Illustrations of the use of R software to perform all the analyses in the book • A new chapter on alternative methods for categorical data, including smoothing and regularization methods (such as the lasso), classification methods such as linear discriminant analysis and classification trees, and cluster analysis • New sections in many chapters introducing the Bayesian approach for the methods of that chapter • More than 70 analyses of data sets to illustrate application of the methods, and about 200 exercises, many containing other data sets • An appendix showing how to use SAS, Stata, and SPSS, and an appendix with short solutions to most odd-numbered exercises Written in an applied, nontechnical style, this book illustrates the methods using a wide variety of real data, including medical clinical trials, environmental questions, drug use by teenagers, horseshoe crab mating, basketball shooting, correlates of happiness, and much more. An Introduction to Categorical Data Analysis, Third Edition is an invaluable tool for statisticians and biostatisticians as well as methodologists in the social and behavioral sciences, medicine and public health, marketing, education, and the biological and agricultural sciences.
Download or read book Applied Survey Data Analysis written by Steven G. Heeringa and published by CRC Press. This book was released on 2017-07-12 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: Highly recommended by the Journal of Official Statistics, The American Statistician, and other journals, Applied Survey Data Analysis, Second Edition provides an up-to-date overview of state-of-the-art approaches to the analysis of complex sample survey data. Building on the wealth of material on practical approaches to descriptive analysis and regression modeling from the first edition, this second edition expands the topics covered and presents more step-by-step examples of modern approaches to the analysis of survey data using the newest statistical software. Designed for readers working in a wide array of disciplines who use survey data in their work, this book continues to provide a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. An example-driven guide to the applied statistical analysis and interpretation of survey data, the second edition contains many new examples and practical exercises based on recent versions of real-world survey data sets. Although the authors continue to use Stata for most examples in the text, they also continue to offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s updated website.
Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
Download or read book IBM SPSS by Example written by Alan C. Elliott and published by SAGE Publications. This book was released on 2014-12-31 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The updated Second Edition of Alan C. Elliott and Wayne A. Woodward’s "cut to the chase" IBM SPSS guide quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision making in a wide variety of disciplines. This one-stop reference provides succinct guidelines for performing an analysis using SPSS software, avoiding pitfalls, interpreting results, and reporting outcomes. Written from a practical perspective, IBM SPSS by Example, Second Edition provides a wealth of information—from assumptions and design to computation, interpretation, and presentation of results—to help users save time, money, and frustration.
Download or read book Transfer Learning written by Qiang Yang and published by Cambridge University Press. This book was released on 2020-02-13 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available. This makes such systems more reliable and robust, keeping the machine learning model faced with unforeseeable changes from deviating too much from expected performance. At an enterprise level, transfer learning allows knowledge to be reused so experience gained once can be repeatedly applied to the real world. For example, a pre-trained model that takes account of user privacy can be downloaded and adapted at the edge of a computer network. This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms. It offers a solid grounding for newcomers as well as new insights for seasoned researchers and developers.
