Download or read book SAS R Technical Report A 108 Cubic Clustering Criterion written by SAS Publishing and published by Sas Inst. This book was released on 1998-08-01 with total page 55 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Clustering and Classification written by Phipps Arabie and published by World Scientific. This book was released on 1996 with total page 508 pages. Available in PDF, EPUB and Kindle. Book excerpt: At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering, variable selection and weighting, additive trees and other network models, relevance of neural network models to clustering, the role of computational complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.
Download or read book SAS Programming for R Users written by Jordan Bakerman and published by . This book was released on 2019-12-09 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: SAS Programming for R Users, based on the free SAS Education course of the same name, is designed for experienced R users who want to transfer their programming skills to SAS. Emphasis is on programming and not statistical theory or interpretation. You will learn how to write programs in SAS that replicate familiar functions and capabilities in R. This book covers a wide range of topics including the basics of the SAS programming language, how to import data, how to create new variables, random number generation, linear modeling, Interactive Matrix Language (IML), and many other SAS procedures. This book also explains how to write R code directly in the SAS code editor for seamless integration between the two tools. Exercises are provided at the end of each chapter so that you can test your knowledge and practice your programming skills.
Download or read book SAS Communications written by SAS Institute and published by . This book was released on 1988 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Handbook of Statistical Graphics Using SAS ODS written by Geoff Der and published by CRC Press. This book was released on 2014-08-15 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Easily Use SAS to Produce Your Graphics Diagrams, plots, and other types of graphics are indispensable components in nearly all phases of statistical analysis, from the initial assessment of the data to the selection of appropriate statistical models to the diagnosis of the chosen models once they have been fitted to the data. Harnessing the full graphics capabilities of SAS, A Handbook of Statistical Graphics Using SAS ODS covers essential graphical methods needed in every statistician’s toolkit. It explains how to implement the methods using SAS 9.4. The handbook shows how to use SAS to create many types of statistical graphics for exploring data and diagnosing fitted models. It uses SAS’s newer ODS graphics throughout as this system offers a number of advantages, including ease of use, high quality of results, consistent appearance, and convenient semiautomatic graphs from the statistical procedures. Each chapter deals graphically with several sets of example data from a wide variety of areas, such as epidemiology, medicine, and psychology. These examples illustrate the use of graphic displays to give an overview of data, to suggest possible hypotheses for testing new data, and to interpret fitted statistical models. The SAS programs and data sets are available online.
Download or read book Data Mining Using SAS Applications written by George Fernandez and published by CRC Press. This book was released on 2010-12-12 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files. These methods stress the use of visualization to thoroughly study the structure of data and check the validity of statistical models fitted to data. Learn how to convert PC databases to SAS data Discover sampling techniques to create training and validation samples Understand frequency data analysis for categorical data Explore supervised and unsupervised learning Master exploratory graphical techniques Acquire model validation techniques in regression and classification The text furnishes 13 easy-to-use SAS data mining macros designed to work with the standard SAS modules. No additional modules or previous experience in SAS programming is required. The author shows how to perform complete predictive modeling, including data exploration, model fitting, assumption checks, validation, and scoring new data, on SAS datasets in less than ten minutes!
Download or read book Cluster Analysis in Neuropsychological Research written by Daniel N. Allen and published by Springer Science & Business Media. This book was released on 2014-07-08 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis is a multivariate classification technique that allows for identification of homogenous subgroups within diverse samples based on shared characteristics. In recent years, cluster analysis has been increasingly applied to psychological and neuropsychological variables to address a number of empirical questions. This book provides an overview of cluster analysis, including statistical and methodological considerations in its application to neurobehavioral variables. First, an introduction to cluster analysis is presented that emphasizes issues of relevance to neuropsychological research, including controversies surrounding it use. Cluster analysis is then applied to clinical disorders that do not have an associated prototypical neuropsychological profile, including traumatic brain injury, schizophrenia, and health problems associated with homelessness. In a second application, cluster analysis is used to investigate the course of normal memory development. Finally, cluster analysis is applied to classification of brain injury severity in children and adolescents who sustained traumatic brain injury.
Download or read book Finding Groups in Data written by Leonard Kaufman and published by Wiley-Interscience. This book was released on 1990-03-22 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.
Download or read book Modern Industrial Statistics written by Ron S. Kenett and published by John Wiley & Sons. This book was released on 2021-04-28 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Industrial Statistics The new edition of the prime reference on the tools of statistics used in industry and services, integrating theoretical, practical, and computer-based approaches Modern Industrial Statistics is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications. The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies—drawn from the electronics, metal work, pharmaceutical, and financial industries—are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume: Explains the use of computer-based methods such as bootstrapping and data visualization Covers nonstandard techniques and applications of industrial statistical process control (SPC) charts Contains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settings Includes access to a companion website that contains an introduction to R, sample R code, csv files of all data sets, JMP add-ins, and downloadable appendices Provides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the book Part of the acclaimed Statistics in Practice series, Modern Industrial Statistics with Applications in R, MINITAB, and JMP, Third Edition, is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The mistat R-package is available from the R CRAN repository.
Download or read book Electric Power Grid Reliability Evaluation written by Chanan Singh and published by John Wiley & Sons. This book was released on 2018-11-13 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The groundbreaking book that details the fundamentals of reliability modeling and evaluation and introduces new and future technologies Electric Power Grid Reliability Evaluation deals with the effective evaluation of the electric power grid and explores the role that this process plays in the planning and designing of the expansion of the power grid. The book is a guide to the theoretical approaches and processes that underpin the electric power grid and reviews the most current and emerging technologies designed to ensure reliability. The authors—noted experts in the field—also present the algorithms that have been developed for analyzing the soundness of the power grid. A comprehensive resource, the book covers probability theory, stochastic processes, and a frequency-based approach in order to provide a theoretical foundation for reliability analysis. Throughout the book, the concepts presented are explained with illustrative examples that connect with power systems. The authors cover generation adequacy methods, and multi-node analysis which includes both multi-area as well as composite power system reliable evaluation. This important book: • Provides a guide to the basic methods of reliability modeling and evaluation • Contains a helpful review of the background of power system reliability evaluation • Includes information on new technology sources that have the potential to create a more reliable power grid • Addresses renewable energy sources and shows how they affect power outages and blackouts that pose new challenges to the power grid system Written for engineering students and professionals, Electric Power Grid Reliability Evaluation is an essential book that explores the processes and algorithms for creating a sound and reliable power grid.
Download or read book Market Data Analysis Using JMP written by Walter R. Paczkowski and published by SAS Institute. This book was released on 2018-02-05 with total page 956 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the powerful interactive and visual functionality of JMP, you can dynamically analyze market data to transform it into actionable and useful information with clear, concise, and insightful reports and displays. Market Data Analysis Using JMP is a unique example-driven book because it has a specific application focus: market data analysis. A working knowledge of JMP will help you turn your market data into vital knowledge that will help you succeed in a highly competitive, fast-moving, and dynamic business world. This book can be used as a stand-alone resource for working professionals, or as a supplement to a business school course in market data research. Anyone who works with market data will benefit from reading and studying this book, then using JMP to apply the dynamic analytical concepts to their market data. After reading this book, you will be able to quickly and effortlessly use JMP to: prepare market data for analysis use and interpret sophisticated statistical methods build choice models estimate regression models to turn data into useful and actionable information Market Data Analysis Using JMP will teach you how to use dynamic graphics to illustrate your market data analysis and explore the vast possibilities that your data can offer!
Download or read book Data Clustering Theory Algorithms and Applications Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Download or read book Mixed Effects Models for Complex Data written by Lang Wu and published by CRC Press. This book was released on 2009-11-11 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values, measurement errors, censoring, and outliers. Self-contained coverage of specific topics Subsequent chapters delve more deeply into missing data problems, covariate measurement errors, and censored responses in mixed effects models. Focusing on incomplete data, the book also covers survival and frailty models, joint models of survival and longitudinal data, robust methods for mixed effects models, marginal generalized estimating equation (GEE) models for longitudinal or clustered data, and Bayesian methods for mixed effects models. Background material In the appendix, the author provides background information, such as likelihood theory, the Gibbs sampler, rejection and importance sampling methods, numerical integration methods, optimization methods, bootstrap, and matrix algebra. Failure to properly address missing data, measurement errors, and other issues in statistical analyses can lead to severely biased or misleading results. This book explores the biases that arise when naïve methods are used and shows which approaches should be used to achieve accurate results in longitudinal data analysis.
Download or read book Introduction to Probability and Statistics Using R written by G. Jay Kerns and published by Lulu.com. This book was released on 2010-01-10 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Download or read book Quantifying Functional Biodiversity written by Laura Pla and published by Springer Science & Business Media. This book was released on 2011-11-02 with total page 103 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book synthesizes current methods used to quantify functional diversity, providing step-by-step examples for defining functional groups and estimating functional indices. The authors show how to compare communities, and how to analyze changes of diversity along environmental gradients, using real-life examples throughout. One section of the book demonstrates the selection of traits, and the standardization and characterization of ecosystem data. Another section presents methods used to quantify functional diversity, shows how to relate functional diversity with environmental variables and how to connect these to ecosystem services. The concluding section introduces FDiversity, a free program developed by the authors. The reader is guided through every step from software installation and basic functions, to sample and database design, to graphical projection methods, employing case study data to illustrate key concepts.
Download or read book Multi Objective Machine Learning written by Yaochu Jin and published by Springer Science & Business Media. This book was released on 2007-06-10 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
Download or read book Information Fusion and Geographic Information Systems written by Vasily Popovich and published by Springer Science & Business Media. This book was released on 2011-06-17 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Workshop Proceedings reflect problems of advanced geo-information science as far as they are specifically concerned with the maritime environment at large. The Proceedings incorporate papers presented by leading scientists researching in the considered professional area and by practitioners engaged in GIS and GIS applications development. They pay close attention to the problems of scientific and technological innovations and the ensuing opportunities to make seas safer and cleaner. Furthermore, they periodically measure the ground covered and new challenges with respect to economic and shipping trends as related to Artificial Intelligence; GIS ontologies; GIS data integration and modelling; Underwater acoustics; GIS data fusion; GIS and corporate information systems; GIS and real-time monitoring systems; GIS algorithms and computational issues; Novel and emerging marine GIS research areas; Monitoring of maritime terrorist threat; Maritime and environmental GIS; Navigation-based and maritime transportation GIS; Human factors in maritime GIS; Coastal and environmental GIS.
