The.Hottest

Thursday, June 04, 2020 , ,
Chris Chatfield, A. Collins ... 248 pages - Publisher: Chapman and Hall/CRC; (May, 1981) ... Language: English - ISBN-10: 9780412160400 - ISBN-13: 978-0412160400.

This book provides an introduction to the analysis of multivariate data.It describes multivariate probability distributions, the preliminary analysisof a large -scale set of data, princ iple component and factor analysis,traditional normal theory material, as well as multidimensional scaling andcluster analysis.Introduction to Multivariate Analysis provides a reasonable blend oftheory and practice. Enough theory is given to introduce the concepts andto make the topics mathematically interesting. In addition the authors discussthe use (and misuse) of the techniques in pra ctice and present appropriatereal-life examples from a variety of areas includ ing agricultural research,soc iology and crim inology. The book should be suitable both for researchworkers and as a text for students taking a course on multivariate analysis.
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Wednesday, June 03, 2020 , ,
Sadanori Konishi ... 338 pages - Publisher: Chapman and Hall/CRC; (June, 2014) ... Language: English - ISBN-10: 1466567287 - ISBN-13: 978-1466567283.

Introduction to Multivariate Analysis: Linear and Nonlinear Modeling shows how multivariate analysis is widely used for extracting useful information and patterns from multivariate data and for understanding the structure of random phenomena. Along with the basic concepts of various procedures in traditional multivariate analysis, the book covers nonlinear techniques for clarifying phenomena behind observed multivariate data. It primarily focuses on regression modeling, classification and discrimination, dimension reduction, and clustering. The text thoroughly explains the concepts and derivations of the AIC, BIC, and related criteria and includes a wide range of practical examples of model selection and evaluation criteria. To estimate and evaluate models with a large number of predictor variables, the author presents regularization methods, including the L1 norm regularization that gives simultaneous model estimation and variable selection. For advanced undergraduate and graduate students in statistical science, this text provides a systematic description of both traditional and newer techniques in multivariate analysis and machine learning. It also introduces linear and nonlinear statistical modeling for researchers and practitioners in industrial and systems engineering, information science, life science, and other areas.
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Tuesday, June 02, 2020 , ,
Roger Koenker, Victor Chernozhukov, Xuming He, Limin Peng ... 483 pages - Publisher: Chapman and Hall/CRC; (October, 2017) ... Language: English - AmazonSIN: B076DG4VR4.

Quantile regression constitutes an ensemble of statistical techniques intended to estimate and draw inferences about conditional quantile functions. Median regression, as introduced in the 18th century by Boscovich and Laplace, is a special case. In contrast to conventional mean regression that minimizes sums of squared residuals, median regression minimizes sums of absolute residuals; quantile regression simply replaces symmetric absolute loss by asymmetric linear loss. Since its introduction in the 1970's by Koenker and Bassett, quantile regression has been gradually extended to a wide variety of data analytic settings including time series, survival analysis, and longitudinal data. By focusing attention on local slices of the conditional distribution of response variables it is capable of providing a more complete, more nuanced view of heterogeneous covariate effects. Applications of quantile regression can now be found throughout the sciences, including astrophysics, chemistry, ecology, economics, finance, genomics, medicine, and meteorology. Software for quantile regression is now widely available in all the major statistical computing environments.

The objective of this volume is to provide a comprehensive review of recent developments of quantile regression methodology illustrating its applicability in a wide range of scientific settings. The intended audience of the volume is researchers and graduate students across a diverse set of disciplines.
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Monday, June 01, 2020 , ,
Wolfgang Karl Härdle, Léopold Simar ... 558 pages - Publisher: Springer; 5th edition(November, 2019) ... Language: English - ISBN-10: 3030260054 - ISBN-13: 978-3030260057.

This textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields, and all the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis.

For this new edition, the book has been updated and extensively revised and now includes an extended chapter on cluster analysis. All solutions to the exercises are supplemented by R and MATLAB or SAS computer code and can be downloaded from the Quantlet platform. Practical exercises from this book and their solutions can also be found in the accompanying Springer book by W.K. Härdle and Z. Hlávka: Multivariate Statistics - Exercises and Solutions.
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Sunday, May 31, 2020 , ,
Roman Vershynin ... 296 pages - Publisher: Cambridge Univ.Press; (September, 2018) ... Language: English - ISBN-10: 1108415199 - ISBN-13: 978-1108415194.

High-dimensional probability offers insight into the behavior of random vectors, random matrices, random subspaces, and objects used to quantify uncertainty in high dimensions. Drawing on ideas from probability, analysis, and geometry, it lends itself to applications in mathematics, statistics, theoretical computer science, signal processing, optimization, and more. It is the first to integrate theory, key tools, and modern applications of high-dimensional probability. Concentration inequalities form the core, and it covers both classical results such as Hoeffding's and Chernoff's inequalities and modern developments such as the matrix Bernstein's inequality. It then introduces the powerful methods based on stochastic processes, including such tools as Slepian's, Sudakov's, and Dudley's inequalities, as well as generic chaining and bounds based on VC dimension. A broad range of illustrations is embedded throughout, including classical and modern results for covariance estimation, clustering, networks, semidefinite programming, coding, dimension reduction, matrix completion, machine learning, compressed sensing, and sparse regression.
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Saturday, May 30, 2020 , , ,
Jeff Heaton ... 244 pages - Publisher: Heaton Research, Inc.; (August, 2014) ... Language: English - AmazonSIN: B00MYLNLSQ.

Nature can be a great source of inspiration for artificial intelligence algorithms because its technology is considerably more advanced than our own. Among its wonders are strong AI, nanotechnology, and advanced robotics. Nature can therefore serve as a guide for real-life problem solving. In this book, you will encounter algorithms influenced by ants, bees, genomes, birds, and cells that provide practical methods for many types of AI situations. Although nature is the muse behind the methods, we are not duplicating its exact processes. The complex behaviors in nature merely provide inspiration in our quest to gain new insights about data.

Artificial Intelligence for Humans is a book series meant to teach AI to those readers who lack an extensive mathematical background. The reader only needs knowledge of basic college algebra and computer programming. Additional topics are thoroughly explained. Every chapter also includes a programming example. Examples are currently provided in Java, C#, and Python. Other languages are planned. No knowledge of biology is needed to read this book.
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Friday, May 29, 2020 , ,
Debbie L. Hahs-Vaughn ... 662 pages - Publisher: Routledge; (November, 2016) ... Language: English - ISBN-10: 0415842360 - ISBN-13: 978-0415842365.

More comprehensive than other texts, this new book covers the classic and cutting edge multivariate techniques used in today’s research. Ideal for courses on multivariate statistics/analysis/design, advanced statistics or quantitative techniques taught in psychology, education, sociology, and business, the book also appeals to researchers with no training in multivariate methods. Through clear writing and engaging pedagogy and examples using real data, Hahs-Vaughn walks students through the most used methods to learn why and how to apply each technique. A conceptual approach with a higher than usual text-to-formula ratio helps reader’s master key concepts so they can implement and interpret results generated by today’s sophisticated software. Annotated screenshots from SPSS and other packages are integrated throughout. Designed for course flexibility, after the first 4 chapters, instructors can use chapters in any sequence or combination to fit the needs of their students. Each chapter includes a ‘mathematical snapshot’ that highlights the technical components of each procedure, so only the most crucial equations are included.

Highlights include: -Outlines, key concepts, and vignettes related to key concepts preview what’s to come in each chapter. -Examples using real data from education, psychology, and other social sciences illustrate key concepts. -Extensive coverage of assumptions including tables, the effects of their violation, and how to test for each technique. -Conceptual, computational, and interpretative problems mirror the real-world problems students encounter in their studies and careers. -A focus on data screening and power analysis with attention on the special needs of each particular method. -Instructions for using SPSS via screenshots and annotated output along with HLM, Mplus, LISREL, and G*Power where appropriate, to demonstrate how to interpret results. -Templates for writing research questions and APA-style write-ups of results which serve as models. -Propensity score analysis chapter that demonstrates the use of this increasingly popular technique. -A review of matrix algebra for those who want an introduction (prerequisites include an introduction to factorial ANOVA, ANCOVA, and simple linear regression, but knowledge of matrix algebra is not assumed).
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Thursday, May 28, 2020 , , ,
Anand J. Kulkarni, Suresh Chandra Satapathy ... 197 pages - Publisher: Springer; (November, 2019) ... Language: English - AmazonSIN: B0825P5H9C.

This book discusses one of the major applications of artificial intelligence: the use of machine learning to extract useful information from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which further helps improve prediction and decision-making. The book also presents formulations of real-world machine learning problems, and discusses AI solution methodologies as standalone or hybrid approaches. Lastly, it proposes novel metaheuristic methods to solve complex machine learning problems. Featuring valuable insights, the book helps readers explore new avenues leading toward multidisciplinary research discussions.
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Wednesday, May 27, 2020 , , ,
Pasquale Giovine, Paolo Maria Mariano, Giuseppe Mortara ... 430 pages - Publisher: Birkhäuser; (March, 2019) ... Language: English - AmazonSIN: B07QQV28CH.

This special issue collects selected contributions (excluding general lectures) of a Symposium on "Micro to MACRO Mathematical Modelling in Soil Mechanics", which took place at the University of Reggio Calabria, Italy, from May 29th to June 1st, 2018. The Symposium provided an opportunity to enhance the scientific debate on the construction of mathematical models for the description of the physical behaviour of soils, as well as on the suggestions provided by the micro-mechanical observation of the matter. The focus was on the comparison between the appropriateness of models and the need of mathematics to obtain rigorous results, which involves know-how from applied mathematical physics, geotechnical engineering and mechanics of solids.
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Tuesday, May 26, 2020 , ,
Loui McCurley ... 328 pages - Publisher: Wiley; (June, 2016) ... Language: English - ISBN-10: 111885960X - ISBN-13: 978-1118859605.

The comprehensive guide to performing work at height more safely and at less cost: In the present economy, employers around the globe are working harder than ever to maximize safety in work at height with a careful eye toward fiscal responsibility.   In the drive to do more with less (workers, money, time, resources, etc.) rope access offers the opportunity to raise the bar in both safety and cost-efficiency.  This specialized mode of access and protection is a solution that site owners and managers frequently turn to for putting specially trained, certified technicians in hard-to-reach places with maximum safety and minimal cost. Professional Rope Access: A Guide to Working Safely at Height is a comprehensive guide that employers, safety managers, trainers, and technicians can use to develop and maintain a rope access program that will get more work accomplished at a lower cost and with greater safety than conventional methods can achieve.

Professional Rope Access features topics on: Planning For Rope Access such as personnel selection and training and Equipment for Rigging + Skills For The Rope Access Technician including Rigging Concepts, Advanced Techniques, Powered Devices, and Rescue + Program Administration from Writing a Work Order through Equipment Inspection & Care.
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Tuesday, May 26, 2020 , ,
Vikrant Sharma, Atul Kumar, N. S. Baruaole, Mukesh Kumar ... 292 pages - Publisher: Alpha Science; (April, 2018) ... Language: English - ISBN-10: 1783323566 - ISBN-13: 978-1783323562.

Statics is one of the most important and fundamental courses in engineering mechanics. The objective of this book is to impart knowledge of fundamental concepts and to gain skill of identifying, formulating and solving engineering problems and also to apply concepts of statics in solving real life problems. The book starts with an introduction to mechanics and goes on to cover concepts of statics like system of forces, equilibrium, analysis of structures, centroid, moment of inertial, friction and stress strain. The topics are covered in an easy to understand manner. Since problem solving is critical in engineering mechanics, the solutions to the problems are given in a systematic and step-wise manner.
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Monday, May 25, 2020 , , ,
Svein Linge, Hans Petter Langtangen ... 216 pages - Publisher: Springer; (August, 2016) ... Language: English - AmazonSIN: B078YHJHL2.

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.
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