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Author : John T. Monyak
Publisher :
ISBN 13 :
Total Pages : 524 pages
Book Rating : 4.:/5 (412 download)
Download or read book Mean Squared Error Properties of the Ridge Regression Estimated Linear Probability Model written by John T. Monyak and published by . This book was released on 1998 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Khursheed Alam
Publisher :
ISBN 13 :
Total Pages : 21 pages
Book Rating : 4.:/5 (227 download)
Download or read book Ridge Estimation for the Linear Regression Model written by Khursheed Alam and published by . This book was released on 1977 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: A class of estimators, variously known as ridge estimators, is considered for the linear regression model Y=X theta + epsilon, where theta is an unknown parameter vector to be estimated. Some properties of the ridge estimators are given. It is shown that certain ridge estimators have uniformly smaller mean squared error than the least squares estimator. (Author).
Author : A. K. Md. Ehsanes Saleh
Publisher : John Wiley & Sons
ISBN 13 : 1118644506
Total Pages : 404 pages
Book Rating : 4.1/5 (186 download)
Download or read book Theory of Ridge Regression Estimation with Applications written by A. K. Md. Ehsanes Saleh and published by John Wiley & Sons. This book was released on 2019-01-08 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications Theory of Ridge Regression Estimation with Applications offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis. Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators. The authors also include problem sets to enhance learning. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource: Offers theoretical coverage and computer-intensive applications of the procedures presented Contains solutions and alternate methods for prediction accuracy and selecting model procedures Presents the first book to focus on ridge regression and unifies past research with current methodology Uses R throughout the text and includes a companion website containing convenient data sets Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
Author : Douglas C. Montgomery
Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 536 pages
Book Rating : 4.:/5 (318 download)
Download or read book Introduction to Linear Regression Analysis written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 1982 with total page 536 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its new exercises and structure, this book is highly recommended for upper-undergraduate and beginning graduate students in mathematics, engineering, and natural sciences. Scientists and engineers will find the book to be an excellent choice for reference and self-study.
Author : George G. Judge
Publisher : John Wiley & Sons
ISBN 13 : 047189530X
Total Pages : 1062 pages
Book Rating : 4.4/5 (718 download)
Download or read book The Theory and Practice of Econometrics written by George G. Judge and published by John Wiley & Sons. This book was released on 1991-01-16 with total page 1062 pages. Available in PDF, EPUB and Kindle. Book excerpt: This broadly based graduate-level textbook covers the major models and statistical tools currently used in the practice of econometrics. It examines the classical, the decision theory, and the Bayesian approaches, and contains material on single equation and simultaneous equation econometric models. Includes an extensive reference list for each topic.
Author : Aurélien Géron
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149203259X
Total Pages : 851 pages
Book Rating : 4.4/5 (92 download)
Download or read book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow written by Aurélien Géron and published by "O'Reilly Media, Inc.". This book was released on 2019-09-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
Author : Michael H. Kutner
Publisher : McGraw-Hill/Irwin
ISBN 13 : 9780072386882
Total Pages : 1396 pages
Book Rating : 4.3/5 (868 download)
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Author : Lawrence
Publisher : CRC Press
ISBN 13 : 9780824781293
Total Pages : 320 pages
Book Rating : 4.7/5 (812 download)
Download or read book Robust Regression written by Lawrence and published by CRC Press. This book was released on 1989-12-11 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combining theory, methodology, and applications in a unified survey, this important reference/text presents the most recent results in robust regression analysis, including properties of robust regression techniques, computational issues, forecasting, and robust ridge regression. It provides useful case studies so that students and engineers can apply these techniques to forecasting, quantitative business analysis, econometrics, marketing, statistics, and demand modeling. Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation ... discusses generalized properties of L[subscript p]-estimators ... includes an algorithm for identifying outliers using least absolute value criterion in regression modeling ... reviews redescending M-estimators ... studies L[subscript 1] linear regression ... proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model ... summarizes known properties of L[subscript 1] estimators for time series analysis ... examines ordinary least squares, latent root regression, and a robust regression weighting scheme ... and evaluates results from five different robust ridge regression estimators. Containing 120 tables and diagrams plus numerous bibliographic citations, Robust Regression: Analysis and Applications is the leading reference for applied statisticians, operations researchers, econometricians, marketing forecasters, business administration and management scientists, and industrial engineers as well as a text for graduate statistics or economics courses. Book jacket.
Author : Fernando Sansò
Publisher : Springer Science & Business Media
ISBN 13 : 366210735X
Total Pages : 356 pages
Book Rating : 4.6/5 (621 download)
Download or read book V Hotine-Marussi Symposium on Mathematical Geodesy written by Fernando Sansò and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Just as in the era of great achievements by scientists such as Newton and Gauss, the mathematical theory of geodesy is continuing the tradition of producing exciting theoretical results, but today the advances are due to the great technological push in the era of satellites for earth observations and large computers for calculations. Every four years a symposium on methodological matters documents this ongoing development in many related underlying areas such as estimation theory, stochastic modelling, inverse problems, and satellite-positioning global-reference systems. This book presents developments in geodesy and related sciences, including applied mathematics, among which are many new results of high intellectual value to help readers stay on top of the latest happenings in the field.
Author :
Publisher :
ISBN 13 :
Total Pages : 960 pages
Book Rating : 4.:/5 (319 download)
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1989 with total page 960 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Norman R. Draper
Publisher : John Wiley & Sons
ISBN 13 : 0471170828
Total Pages : 736 pages
Book Rating : 4.4/5 (711 download)
Download or read book Applied Regression Analysis written by Norman R. Draper and published by John Wiley & Sons. This book was released on 1998-04-23 with total page 736 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ein Hauptziel wissenschaftlicher Forschung ist das Auffinden von Beziehungen zwischen Variablen. Die Regressionsrechnung ist ein allgemein gebräuchliches statistisches Mittel zur Erstellung von mathematischen Modellen aus Forschungsdaten. Die 3. Auflage wurde um 16 neue Kapitel erweitert; die Grundlagen der Regressionsrechnung werden, ausgehend von klassischen Konzepten, präzise erklärt. Mit vielen Übungsaufgaben und Lösungen sowie einer Diskette. (06/98)
Author :
Publisher :
ISBN 13 :
Total Pages : 980 pages
Book Rating : 4.F/5 ( download)
Download or read book Dissertation Abstracts International written by and published by . This book was released on 2008 with total page 980 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Matthew K. MacGue
Publisher :
ISBN 13 :
Total Pages : 486 pages
Book Rating : 4.:/5 (319 download)
Download or read book Ridge Regression written by Matthew K. MacGue and published by . This book was released on 1981 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sadanori Konishi
Publisher : Springer Science & Business Media
ISBN 13 : 9780387718873
Total Pages : 276 pages
Book Rating : 4.7/5 (188 download)
Download or read book Information Criteria and Statistical Modeling written by Sadanori Konishi and published by Springer Science & Business Media. This book was released on 2007-09-12 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It’s a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They’re also used to control such systems, as well as to make reliable predictions in various natural and social science fields.
Author : Rafael A. Irizarry
Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 794 pages
Book Rating : 4.0/5 (7 download)
Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Author : Marco Taboga
Publisher : Createspace Independent Publishing Platform
ISBN 13 : 9781981369195
Total Pages : 670 pages
Book Rating : 4.3/5 (691 download)
Download or read book Lectures on Probability Theory and Mathematical Statistics - 3rd Edition written by Marco Taboga and published by Createspace Independent Publishing Platform. This book was released on 2017-12-08 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of 80 short and self-contained lectures covering most of the topics that are usually taught in intermediate courses in probability theory and mathematical statistics. There are hundreds of examples, solved exercises and detailed derivations of important results. The step-by-step approach makes the book easy to understand and ideal for self-study. One of the main aims of the book is to be a time saver: it contains several results and proofs, especially on probability distributions, that are hard to find in standard references and are scattered here and there in more specialistic books. The topics covered by the book are as follows. PART 1 - MATHEMATICAL TOOLS: set theory, permutations, combinations, partitions, sequences and limits, review of differentiation and integration rules, the Gamma and Beta functions. PART 2 - FUNDAMENTALS OF PROBABILITY: events, probability, independence, conditional probability, Bayes' rule, random variables and random vectors, expected value, variance, covariance, correlation, covariance matrix, conditional distributions and conditional expectation, independent variables, indicator functions. PART 3 - ADDITIONAL TOPICS IN PROBABILITY THEORY: probabilistic inequalities, construction of probability distributions, transformations of probability distributions, moments and cross-moments, moment generating functions, characteristic functions. PART 4 - PROBABILITY DISTRIBUTIONS: Bernoulli, binomial, Poisson, uniform, exponential, normal, Chi-square, Gamma, Student's t, F, multinomial, multivariate normal, multivariate Student's t, Wishart. PART 5 - MORE DETAILS ABOUT THE NORMAL DISTRIBUTION: linear combinations, quadratic forms, partitions. PART 6 - ASYMPTOTIC THEORY: sequences of random vectors and random variables, pointwise convergence, almost sure convergence, convergence in probability, mean-square convergence, convergence in distribution, relations between modes of convergence, Laws of Large Numbers, Central Limit Theorems, Continuous Mapping Theorem, Slutsky's Theorem. PART 7 - FUNDAMENTALS OF STATISTICS: statistical inference, point estimation, set estimation, hypothesis testing, statistical inferences about the mean, statistical inferences about the variance.
Author : J. P. Norton
Publisher : Courier Corporation
ISBN 13 : 0486469352
Total Pages : 322 pages
Book Rating : 4.4/5 (864 download)
Download or read book An Introduction to Identification written by J. P. Norton and published by Courier Corporation. This book was released on 2009-01-01 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for advanced undergraduates and graduate students, this text covers the theoretical basis for mathematical modeling as well as a variety of identification algorithms and their applications. 1986 edition.
