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Statistics by Thomas Hill,Pawel Lewicki,Paweł Lewicki Pdf
This - one of a kind - book offers a comprehensive, almost encyclopedic presentation of statistical methods and analytic approaches used in science, industry, business, and data mining, written from the perspective of the real-life practitioner ("consumer") of these methods.
Research Anthology on Machine Learning Techniques, Methods, and Applications by Management Association, Information Resources Pdf
Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.
Handbook of Research on AI Methods and Applications in Computer Engineering by Kaddoura, Sanaa Pdf
The development of artificial intelligence (AI) involves the creation of computer systems that can do activities that would ordinarily require human intelligence, such as visual perception, speech recognition, decision making, and language translation. Through increasingly complex programming approaches, it has been transforming and advancing the discipline of computer science. The Handbook of Research on AI Methods and Applications in Computer Engineering illuminates how todays computer engineers and scientists can use AI in real-world applications. It focuses on a few current and emergent AI applications, allowing a more in-depth discussion of each topic. Covering topics such as biomedical research applications, navigation systems, and search engines, this premier reference source is an excellent resource for computer scientists, computer engineers, IT managers, students and educators of higher education, librarians, researchers, and academicians.
Ensemble Classification Methods with Applications in R by Esteban Alfaro,Matías Gámez,Noelia García Pdf
An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifiers methods and includes a review of the most commonly used techniques. This important resource shows how ensemble classification has become an extension of the individual classifiers. The text puts the emphasis on two areas of machine learning: classification trees and ensemble learning. The authors explore ensemble classification methods’ basic characteristics and explain the types of problems that can emerge in its application. Written by a team of noted experts in the field, the text is divided into two main sections. The first section outlines the theoretical underpinnings of the topic and the second section is designed to include examples of practical applications. The book contains a wealth of illustrative cases of business failure prediction, zoology, ecology and others. This vital guide: Offers an important text that has been tested both in the classroom and at tutorials at conferences Contains authoritative information written by leading experts in the field Presents a comprehensive text that can be applied to courses in machine learning, data mining and artificial intelligence Combines in one volume two of the most intriguing topics in machine learning: ensemble learning and classification trees Written for researchers from many fields such as biostatistics, economics, environment, zoology, as well as students of data mining and machine learning, Ensemble Classification Methods with Applications in R puts the focus on two topics in machine learning: classification trees and ensemble learning.
Microeconometrics by A. Colin Cameron,Pravin K. Trivedi Pdf
This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on seven large and exceptionally rich data sets.
Numerical Methods and Applications by Geno Nikolov,Natalia Kolkovska,Krassimir Georgiev Pdf
This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Numerical Methods and Applications, NMA 2018, held in Borovets, Bulgaria, in August 2018. The 56 revised regular papers presented were carefully reviewed and selected from 61 submissions for inclusion in this book. The papers are organized in the following topical sections: numerical search and optimization; problem-driven numerical method: motivation and application, numerical methods for fractional diffusion problems; orthogonal polynomials and numerical quadratures; and Monte Carlo and Quasi-Monte Carlo methods.
This book summarizes the knowledge in the field of methods to identify signatures of natural selection. A number of mathematical models and methods have been designed to identify the fingerprints of natural selection on genes and genomes. Such methods are provided in a simple and direct way so that students of different disciplines can navigate thr
Methods and Applications for Modeling and Simulation of Complex Systems by Gary Tan,Axel Lehmann,Yong Meng Teo,Wentong Cai Pdf
This volume constitutes the proceedings of the 19th Asia Simulation Conference, AsiaSim 2019, held in Singapore, Singapore, in October 2019. The 19 revised full papers and 5 short papers presented in this volume were carefully reviewed and selected from 36 submissions. The papers are organized in topical sections on simulation and modeling methodology; numerical and Monte Carlo simulation; simulation applications: blockchain, deep learning and cloud; simulation and visualization; simulation applications; short papers.
Christiaan Heij,Paul de Boer,Philip Hans Franses,Teun Kloek,Herman K. van Dijk,All at the Erasmus University in Rotterdam
Author : Christiaan Heij,Paul de Boer,Philip Hans Franses,Teun Kloek,Herman K. van Dijk,All at the Erasmus University in Rotterdam Publisher : OUP Oxford Page : 816 pages File Size : 54,5 Mb Release : 2004-03-25 Category : Business & Economics ISBN : 9780191533235
Econometric Methods with Applications in Business and Economics by Christiaan Heij,Paul de Boer,Philip Hans Franses,Teun Kloek,Herman K. van Dijk,All at the Erasmus University in Rotterdam Pdf
Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). · Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. · Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. · Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. · Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.
Design Structure Matrix Methods and Applications by Steven D. Eppinger,Tyson R. Browning Pdf
Design structure matrix (DSM) is a straightforward and flexible modeling technique that can be used for designing, developing, and managing complex systems. DSM offers network modeling tools that represent the elements of a system and their interactions, thereby highlighting the system's architecture (or designed structure). Its advantages include compact format, visual nature, intuitive representation, powerful analytical capacity, and flexibility. Used primarily so far in the area of engineering management, DSM is increasingly being applied to complex issues in health care management, financial systems, public policy, natural sciences, and social systems. This book offers a clear and concise explanation of DSM methods for practitioners and researchers.
Multiple Criteria Decision Methods and Applications by Günter Fandel,Jaap Spronk Pdf
Both the 'First International Summer School on Multiple Criteria Decision Making Methods, Applications and Software' and the present volume of readings could only be realised with assistance and support from many sides. We would like to express our gratitude to all those who have contributed to making a success of the first of a hopefully long series of summer schools in this field and to all those who have contribut. ed to the present volume. First of all we are grateful for the financial means supplied by a long list of sponsors, the most important of which are mentioned on the copyright page. Next, we are grateful to the members of the organising committee, Anna Ostanello and Giovanni Zambruno. Since this is the first of what will become a series of summer schools, the chairman of the organising committee, Benedetto Matarazzo, will start this volume with a brief account of the school held in Acireale. The programme committee consisted of Jean Fichefet, Anna Ostanello, Bernard Roy, Jaap Spronk (chairman) and Stanley Zionts. Their valuable contribu tion is gratefully acknowledged, as is the contribution of all the lecturers at the school. Of course, a school is not only made by its teachers, but just as much by its students. The primary aim of a school is to teach and to stimulate the students.
XML Data Mining: Models, Methods, and Applications by Tagarelli, Andrea Pdf
The widespread use of XML in business and scientific databases has prompted the development of methodologies, techniques, and systems for effectively managing and analyzing XML data. This has increasingly attracted the attention of different research communities, including database, information retrieval, pattern recognition, and machine learning, from which several proposals have been offered to address problems in XML data management and knowledge discovery. XML Data Mining: Models, Methods, and Applications aims to collect knowledge from experts of database, information retrieval, machine learning, and knowledge management communities in developing models, methods, and systems for XML data mining. This book addresses key issues and challenges in XML data mining, offering insights into the various existing solutions and best practices for modeling, processing, analyzing XML data, and for evaluating performance of XML data mining algorithms and systems.
Propensity Score Methods and Applications by Haiyan Bai,M. H. Clark Pdf
A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method. Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.
Principles, Methods, and General Applications by Gunter Zweig Pdf
Analytical Methods for Pesticides, Plant Growth Regulators, and Food Additives, Volume 1: Principles, Methods, and General Applications provides information on analytical techniques useful for the determination of pesticides, plant growth regulators, and food additives. The book discusses the potential hazard of minute residues to human and animal health; the principles of formulation and residue analyses; and the principles of food additive analysis. The text also describes the extraction and clean-up procedures; and the principles of toxicological testing methods. The methods for pesticide analysis in meat products; and the formulation and residue analysis in government laboratories are also considered. The book further tackles other methods, such as spectrophotometric methods, chromatography, isotope methods, enzymatic methods; and bioassay. Agricultural toxicologists and people studying pesticides and food additives will find the text invaluable.