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Author : Meekyong Park
Publisher : Unknown
Page : 264 pages
File Size : 45,5 Mb
Release : 1996
Category : Electronic
ISBN : UOM:39015037450221
Author : John Fox
Publisher : SAGE Publications
Page : 96 pages
File Size : 42,9 Mb
Release : 2000-05-01
Category : Social Science
ISBN : 9781544332604
This book builds on John Fox's previous volume in the QASS Series, Non Parametric Simple Regression. In this book, the reader learns how to estimate and plot smooth functions when there are multiple independent variables.
Author : North-Holland Publishing Company
Publisher : Unknown
Page : 1188 pages
File Size : 49,7 Mb
Release : 1998
Category : Electronic
ISBN : 03783758
Author : Naihua Duan
Publisher : Unknown
Page : 16 pages
File Size : 43,6 Mb
Release : 1991
Category : Least squares
ISBN : IND:30000022648103
Author : Álvaro Rocha,Hojjat Adeli,Luís Paulo Reis,Sandra Costanzo
Publisher : Springer
Page : 1518 pages
File Size : 50,9 Mb
Release : 2018-03-24
Category : Technology & Engineering
ISBN : 9783319777122
This book includes a selection of papers from the 2018 World Conference on Information Systems and Technologies (WorldCIST'18), held in Naples, Italy on March27-29, 2018. WorldCIST is a global forum for researchers and practitioners to present and discuss recent results and innovations, current trends, professional experiences and the challenges of modern information systems and technologies research together with their technological development and applications. The main topics covered are: A) Information and Knowledge Management; B) Organizational Models and Information Systems; C) Software and Systems Modeling; D) Software Systems, Architectures, Applications and Tools; E) Multimedia Systems and Applications; F) Computer Networks, Mobility and Pervasive Systems; G) Intelligent and Decision Support Systems; H) Big Data Analytics and Applications; I) Human–Computer Interaction; J) Ethics, Computers & Security; K) Health Informatics; L) Information Technologies in Education; M) Information Technologies in Radiocommunications; N) Technologies for Biomedical Applications.
Author : Trevor Hastie,Robert Tibshirani,Jerome Friedman
Publisher : Springer Science & Business Media
Page : 545 pages
File Size : 42,5 Mb
Release : 2013-11-11
Category : Mathematics
ISBN : 9780387216065
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Author : William Raynor
Publisher : Global Professional Publishi
Page : 340 pages
File Size : 50,9 Mb
Release : 1998-11
Category : Business & Economics
ISBN : 1888998466
This book is a must reference for all disciplines - business, science, education and engineering. This important work contains over 2,500 entries - defined, explained and illustrated - and detailed discussion of major concepts as well as topics in related disciplines. This volume is cross-referenced, has an annotated bibliography and an extensive appendix of WWW sites on the latest trends in artificial intelligence.
Author : James E. Gentle
Publisher : Springer Science & Business Media
Page : 420 pages
File Size : 47,8 Mb
Release : 2006-04-18
Category : Computers
ISBN : 9780387216119
Will provide a more elementary introduction to these topics than other books available; Gentle is the author of two other Springer books
Author : Hengqing Tong,T. Krishna Kumar,Yangxin Huang
Publisher : John Wiley & Sons
Page : 489 pages
File Size : 48,8 Mb
Release : 2011-12-12
Category : Business & Economics
ISBN : 9780470681770
Statistical Theories and Methods with Applications to Economics and Business highlights recent advances in statistical theory and methods that benefit econometric practice. It deals with exploratory data analysis, a prerequisite to statistical modelling and part of data mining. It provides recently developed computational tools useful for data mining, analysing the reasons to do data mining and the best techniques to use in a given situation. Provides a detailed description of computer algorithms. Provides recently developed computational tools useful for data mining Highlights recent advances in statistical theory and methods that benefit econometric practice. Features examples with real life data. Accompanying software featuring DASC (Data Analysis and Statistical Computing). Essential reading for practitioners in any area of econometrics; business analysts involved in economics and management; and Graduate students and researchers in economics and statistics.
Author : Xiaofeng Wang,Yu Ryan Yue,Julian J. Faraway
Publisher : CRC Press
Page : 312 pages
File Size : 45,5 Mb
Release : 2018-01-29
Category : Mathematics
ISBN : 9781351165754
INLA stands for Integrated Nested Laplace Approximations, which is a new method for fitting a broad class of Bayesian regression models. No samples of the posterior marginal distributions need to be drawn using INLA, so it is a computationally convenient alternative to Markov chain Monte Carlo (MCMC), the standard tool for Bayesian inference. Bayesian Regression Modeling with INLA covers a wide range of modern regression models and focuses on the INLA technique for building Bayesian models using real-world data and assessing their validity. A key theme throughout the book is that it makes sense to demonstrate the interplay of theory and practice with reproducible studies. Complete R commands are provided for each example, and a supporting website holds all of the data described in the book. An R package including the data and additional functions in the book is available to download. The book is aimed at readers who have a basic knowledge of statistical theory and Bayesian methodology. It gets readers up to date on the latest in Bayesian inference using INLA and prepares them for sophisticated, real-world work. Xiaofeng Wang is Professor of Medicine and Biostatistics at the Cleveland Clinic Lerner College of Medicine of Case Western Reserve University and a Full Staff in the Department of Quantitative Health Sciences at Cleveland Clinic. Yu Ryan Yue is Associate Professor of Statistics in the Paul H. Chook Department of Information Systems and Statistics at Baruch College, The City University of New York. Julian J. Faraway is Professor of Statistics in the Department of Mathematical Sciences at the University of Bath.
Author : R. Salehnejad
Publisher : Springer
Page : 309 pages
File Size : 51,5 Mb
Release : 2006-11-28
Category : Business & Economics
ISBN : 9780230625150
This book challenges the generally accepted theories of classical economics, explaining why the expected utility theory, even if it were true, fails to be of much help in solving economic controversies.
Author : Wendy L. Martinez,Angel R. Martinez
Publisher : CRC Press
Page : 794 pages
File Size : 44,8 Mb
Release : 2007-12-20
Category : Mathematics
ISBN : 9781420010862
As with the bestselling first edition, Computational Statistics Handbook with MATLAB, Second Edition covers some of the most commonly used contemporary techniques in computational statistics. With a strong, practical focus on implementing the methods, the authors include algorithmic descriptions of the procedures as well as
Author : Bertrand Clarke,Ernest Fokoue,Hao Helen Zhang
Publisher : Springer Science & Business Media
Page : 786 pages
File Size : 51,9 Mb
Release : 2009-07-21
Category : Computers
ISBN : 9780387981352
Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics drawn from Statistics, Computer Science, and Electrical Engineering
Author : Sebastian Thrun,Lawrence K. Saul,Bernhard Schölkopf
Publisher : MIT Press
Page : 1694 pages
File Size : 50,5 Mb
Release : 2004
Category : Models, Neurological
ISBN : 0262201526
Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees -- physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.
Author : Jian Qing Shi,Taeryon Choi
Publisher : CRC Press
Page : 218 pages
File Size : 42,5 Mb
Release : 2011-07-01
Category : Mathematics
ISBN : 9781439837733
Gaussian Process Regression Analysis for Functional Data presents nonparametric statistical methods for functional regression analysis, specifically the methods based on a Gaussian process prior in a functional space. The authors focus on problems involving functional response variables and mixed covariates of functional and scalar variables. Covering the basics of Gaussian process regression, the first several chapters discuss functional data analysis, theoretical aspects based on the asymptotic properties of Gaussian process regression models, and new methodological developments for high dimensional data and variable selection. The remainder of the text explores advanced topics of functional regression analysis, including novel nonparametric statistical methods for curve prediction, curve clustering, functional ANOVA, and functional regression analysis of batch data, repeated curves, and non-Gaussian data. Many flexible models based on Gaussian processes provide efficient ways of model learning, interpreting model structure, and carrying out inference, particularly when dealing with large dimensional functional data. This book shows how to use these Gaussian process regression models in the analysis of functional data. Some MATLAB® and C codes are available on the first author’s website.
