Download or read book Adaptive Regression written by Yadolah Dodge and published by Springer Science & Business Media. This book was released on 2012-10-01 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all purposes. This text focuses on the construction of an adaptive combination of two estimation methods so as to help users make an objective choice and combine the desirable properties of two estimators.
Download or read book Adaptive Regression written by Yadolah Dodge and published by Springer Science & Business Media. This book was released on 2000-04-20 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: While there have been a large number of estimation methods proposed and developed for linear regression, none has proved good for all purposes. This text focuses on the construction of an adaptive combination of two estimation methods so as to help users make an objective choice and combine the desirable properties of two estimators.
Download or read book Adaptive Regression for Modeling Nonlinear Relationships written by George J. Knafl and published by Springer. This book was released on 2016-09-20 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet nonlinear relationships are common and so need to be addressed. A standard linear analysis can produce misleading conclusions, while a nonlinear analysis can provide novel insights into data, not otherwise possible. A variety of examples of the benefits of modeling nonlinear relationships are presented throughout the book. Methods are covered using what are called fractional polynomials based on real-valued power transformations of primary predictor variables combined with model selection based on likelihood cross-validation. The book covers how to formulate and conduct such adaptive fractional polynomial modeling in the standard, logistic, and Poisson regression contexts with continuous, discrete, and counts outcomes, respectively, either univariate or multivariate. The book also provides a comparison of adaptive modeling to generalized additive modeling (GAM) and multiple adaptive regression splines (MARS) for univariate outcomes. The authors have created customized SAS macros for use in conducting adaptive regression modeling. These macros and code for conducting the analyses discussed in the book are available through the first author's website and online via the book’s Springer website. Detailed descriptions of how to use these macros and interpret their output appear throughout the book. These methods can be implemented using other programs.
Download or read book Multivariate Adaptive Regression Splines written by Stanford University. Dept. of Statistics. Laboratory for Computational Statistics and published by . This book was released on 1990 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Regression written by Springer and published by . This book was released on 2012-10-23 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Multivariate Adaptive Regression Spline Based Framework for Statistically Parsimonious Adaptive Dyanmic Programming written by Subrat Sahu and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Central to Dynamic Programming (DP) is the 'cost-to-go' or 'future value' function, which is obtained via solving the Bellman's equation, and central to many Approximate Dynamic Programming (ADP) methods is the approximation of the future value function. The exact DP algorithm seeks to compute and store a table consisting of one cost-to-go value for each point in the state space, and its usefulness is limited by the curse of dimensionality, which renders the methodology computationally intractable in the face of real life problems with high-dimensional state spaces and in the face of continuous state variables. ADP methodology seeks to address and redress the issue of the curse of dimensionality by not seeking to compute the future value function exactly and at each point of the state space; rather opting for an approximation of the future value function in the domain of the state space. Existing ADP methodologies have successfully handled 'continuous' state variables through discretization of the state space and estimation of the cost-to-go or future value function and have been challenged in scenarios involving a mix of 'continuous' and 'categorical' or qualitative state variables. The first part of this dissertation research seeks to develop a flexible, nonparametric statistical modeling method which can capture complex nonlinearity in data comprised of a mix of continuous and categorical variables and can be used to approximate future value functions in stochastic dynamic programming (SDP) problems with a mix of continuous and categorical state variables. This dissertation proposes a statistical modeling method, called 'TreeMARS' which combines the versatility of tree-models with the flexibility of multivariate adaptive regression splines (MARS). An extension of the proposed model, called 'Boosted TreeMARS', is also presented. Comparisons are made to the tree-regression model that uses a similar concept, but only permits the use of linear regression at the terminal nodes. Comparisons are presented on a 10-dimensional simulated data set. The second part of the dissertation research, seeking statistical parsimony, proposes a sequential statistical modeling methodology utilizing the 'sequential' concept from Design and Analysis of Computer Experiments (DACE) to make the grid 'only fine enough' for the 'efficient' discretization and then use MARS methods to approximate future value functions. This methodology can be extended in the future to use tree-based MARS models to approximate future value functions involving a mix of continuous and categorical state variables. This sequential grid discretization is nothing but sequential exploration of the state space and this concept of sequential exploration of the state space provides a statistically parsimonious ADP methodology which 'adaptively' captures the important variables from the state space and builds approximations around these quantities while seeking approximation of the future value functions, by using adaptive and flexible modeling.
Download or read book An Adaptive Regression Model written by Thomas Cooley and published by . This book was released on 1970* with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hands On Machine Learning with R written by Brad Boehmke and published by CRC Press. This book was released on 2019-11-07 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process and is meant to help the reader learn to apply the machine learning stack within R, which includes using various R packages such as glmnet, h2o, ranger, xgboost, keras, and others to effectively model and gain insight from their data. The book favors a hands-on approach, providing an intuitive understanding of machine learning concepts through concrete examples and just a little bit of theory. Throughout this book, the reader will be exposed to the entire machine learning process including feature engineering, resampling, hyperparameter tuning, model evaluation, and interpretation. The reader will be exposed to powerful algorithms such as regularized regression, random forests, gradient boosting machines, deep learning, generalized low rank models, and more! By favoring a hands-on approach and using real word data, the reader will gain an intuitive understanding of the architectures and engines that drive these algorithms and packages, understand when and how to tune the various hyperparameters, and be able to interpret model results. By the end of this book, the reader should have a firm grasp of R’s machine learning stack and be able to implement a systematic approach for producing high quality modeling results. Features: · Offers a practical and applied introduction to the most popular machine learning methods. · Topics covered include feature engineering, resampling, deep learning and more. · Uses a hands-on approach and real world data.
Download or read book Adaptive Regression Dogmatism and Creativity written by Irwin H. Cohen and published by . This book was released on 1960 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Ego Psychology and Social Work Practice written by Eda Goldstein and published by Simon and Schuster. This book was released on 1995-03 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: While ego psychological theory still holds a pre-eminent position in clinical social work practice, the field has changed in many ways. This revised edition addresses these major changes, bringing the reader up to date.
Download or read book Adaptive Signal Regression written by Stephanie Ruth Land and published by . This book was released on 1995 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Combining Multivariate Adaptive Regression Splines with a Response Surface Methodology for Simulation based Design Optimization written by Scott T. Crino and published by . This book was released on 2006 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book An Investigation of Multivariate Adaptive Regression Splines for Modeling and Analysis of Univariate and Semi multivariate Time Series Systems written by James G. Stevens and published by . This book was released on 1991 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Survival Analysis with Multivariate Adaptive Regression Splines written by Monika Kriner and published by . This book was released on 2007 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Adaptive Regression in Psychotherapy written by Thomas Irving De Vol and published by . This book was released on 1979 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Hypnosis written by Ronald E. Shor and published by Routledge. This book was released on 2017-07-12 with total page 813 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thorough revision of the first edition, updates and expands, with 25 percent new material, what was generally recognized as a major survey of contemporary scientific research in hypnosis. In this edition, also a classic, the editors include three new essays in modern hypnosis studies. They also provide a new conceptual framework--cognitive, ego-psychological, and phenomenological--with which to examine hypnosis. This edition is divided into six sections--Theoretical and Historical Perspectives, New Theories, Surveys of Broad Areas, Lines of Individual Research, Individual Researches within Specific Areas, and Anticipations for Future Research. The entire book was completely revised in the light of additional research since publication of the original edition. Thirteen of the twenty chapters in the first edition were updated by their authors, six so extensively that they amount to new chapters, with changes in title and order of authors in the case of coauthored chapters. Hypnosis: Developments in Research and New Perspectives is intended for researchers in hypnosis and clinical practitioners in medicine and psychology. The focus, as indicated by the changed subtitle, is on developments since publication of the original editions: empirical studies, experiments with physiological indicators of hypnosis, and theoretical uses associated with use of hypnosis as a research tool. Altogether, this second edition is a valuable overall guide to an intriguing topic.
Download or read book A New Technique for Using Multivariate Adaptive Regression Splines MARS in Pavement Roughness Prediction written by Nii O. Attoh-Okine and published by . This book was released on 2003 with total page 5 pages. Available in PDF, EPUB and Kindle. Book excerpt:
