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Handbook of Mixture Analysis

Handbook of Mixture Analysis PDF Author: Sylvia Frühwirth-Schnatter
Publisher: CRC Press
ISBN: 9780367732066
Category : Distribution (Probability theory)
Languages : en
Pages : 498

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Book Description
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

Handbook of Mixture Analysis

Handbook of Mixture Analysis PDF Author: Sylvia Frühwirth-Schnatter
Publisher: CRC Press
ISBN: 9780367732066
Category : Distribution (Probability theory)
Languages : en
Pages : 498

View

Book Description
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

Handbook of Mixture Analysis

Handbook of Mixture Analysis PDF Author: Sylvia Fruhwirth-Schnatter
Publisher: CRC Press
ISBN: 0429508247
Category : Computers
Languages : en
Pages : 498

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Book Description
Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis

The Oxford Handbook of Quantitative Methods, Vol. 2: Statistical Analysis PDF Author: Todd D. Little
Publisher: Oxford University Press
ISBN: 0199934908
Category : Psychology
Languages : en
Pages : 784

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Book Description
Research today demands the application of sophisticated and powerful research tools. Fulfilling this need, The Oxford Handbook of Quantitative Methods is the complete tool box to deliver the most valid and generalizable answers to todays complex research questions. It is a one-stop source for learning and reviewing current best-practices in quantitative methods as practiced in the social, behavioral, and educational sciences. Comprising two volumes, this handbook covers a wealth of topics related to quantitative research methods. It begins with essential philosophical and ethical issues related to science and quantitative research. It then addresses core measurement topics before delving into the design of studies. Principal issues related to modern estimation and mathematical modeling are also detailed. Topics in the handbook then segway into the realm of statistical inference and modeling with chapters dedicated to classical approaches as well as modern latent variable approaches. Numerous chapters associated with longitudinal data and more specialized techniques round out this broad selection of topics. Comprehensive, authoritative, and user-friendly, this two-volume set will be an indispensable resource for serious researchers across the social, behavioral, and educational sciences.

Remote Sensing Handbook - Three Volume Set

Remote Sensing Handbook - Three Volume Set PDF Author: Prasad Thenkabail
Publisher: CRC Press
ISBN: 1482282674
Category : Technology & Engineering
Languages : en
Pages : 2304

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Book Description
A volume in the three-volume Remote Sensing Handbook series, Remote Sensing of Water Resources, Disasters, and Urban Studies documents the scientific and methodological advances that have taken place during the last 50 years. The other two volumes in the series are Remotely Sensed Data Characterization, Classification, and Accuracies, and Land Reso

Handbook of Advanced Multilevel Analysis

Handbook of Advanced Multilevel Analysis PDF Author: Joop Hox
Publisher: Routledge
ISBN: 1136951261
Category : Psychology
Languages : en
Pages : 698

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Book Description
This new handbook is the definitive resource on advanced topics related to multilevel analysis. The editors assembled the top minds in the field to address the latest applications of multilevel modeling as well as the specific difficulties and methodological problems that are becoming more common as more complicated models are developed. Each chapter features examples that use actual datasets. These datasets, as well as the code to run the models, are available on the book’s website http://www.hlm-online.com . Each chapter includes an introduction that sets the stage for the material to come and a conclusion. Divided into five sections, the first provides a broad introduction to the field that serves as a framework for understanding the latter chapters. Part 2 focuses on multilevel latent variable modeling including item response theory and mixture modeling. Section 3 addresses models used for longitudinal data including growth curve and structural equation modeling. Special estimation problems are examined in section 4 including the difficulties involved in estimating survival analysis, Bayesian estimation, bootstrapping, multiple imputation, and complicated models, including generalized linear models, optimal design in multilevel models, and more. The book’s concluding section focuses on statistical design issues encountered when doing multilevel modeling including nested designs, analyzing cross-classified models, and dyadic data analysis. Intended for methodologists, statisticians, and researchers in a variety of fields including psychology, education, and the social and health sciences, this handbook also serves as an excellent text for graduate and PhD level courses in multilevel modeling. A basic knowledge of multilevel modeling is assumed.

The Wiley Handbook of Cognition and Assessment

The Wiley Handbook of Cognition and Assessment PDF Author: Andre A. Rupp
Publisher: John Wiley & Sons
ISBN: 1118956575
Category : Education
Languages : en
Pages : 645

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Book Description
This state-of-the-art resource brings together the most innovative scholars and thinkers in the field of testing to capture the changing conceptual, methodological, and applied landscape of cognitively-grounded educational assessments. Offers a methodologically-rigorous review of cognitive and learning sciences models for testing purposes, as well as the latest statistical and technological know-how for designing, scoring, and interpreting results Written by an international team of contributors at the cutting-edge of cognitive psychology and educational measurement under the editorship of a research director at the Educational Testing Service and an esteemed professor of educational psychology at the University of Alberta as well as supported by an expert advisory board Covers conceptual frameworks, modern methodologies, and applied topics, in a style and at a level of technical detail that will appeal to a wide range of readers from both applied and scientific backgrounds Considers emerging topics in cognitively-grounded assessment, including applications of emerging socio-cognitive models, cognitive models for human and automated scoring, and various innovative virtual performance assessments

Model-Based Clustering and Classification for Data Science

Model-Based Clustering and Classification for Data Science PDF Author: Charles Bouveyron
Publisher: Cambridge University Press
ISBN: 1108640591
Category : Mathematics
Languages : en
Pages :

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Book Description
Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.

Trends in Data Engineering Methods for Intelligent Systems

Trends in Data Engineering Methods for Intelligent Systems PDF Author: Jude Hemanth
Publisher: Springer Nature
ISBN: 3030793575
Category : Computers
Languages : en
Pages : 773

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Book Description
This book briefly covers internationally contributed chapters with artificial intelligence and applied mathematics-oriented background-details. Nowadays, the world is under attack of intelligent systems covering all fields to make them practical and meaningful for humans. In this sense, this edited book provides the most recent research on use of engineering capabilities for developing intelligent systems. The chapters are a collection from the works presented at the 2nd International Conference on Artificial Intelligence and Applied Mathematics in Engineering held within 09-10-11 October 2020 at the Antalya, Manavgat (Turkey). The target audience of the book covers scientists, experts, M.Sc. and Ph.D. students, post-docs, and anyone interested in intelligent systems and their usage in different problem domains. The book is suitable to be used as a reference work in the courses associated with artificial intelligence and applied mathematics.

Handbook of Psychology, Research Methods in Psychology

Handbook of Psychology, Research Methods in Psychology PDF Author: Irving B. Weiner
Publisher: John Wiley & Sons
ISBN: 1118282035
Category : Psychology
Languages : en
Pages : 800

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Book Description
Psychology is of interest to academics from many fields, as well as to the thousands of academic and clinical psychologists and general public who can't help but be interested in learning more about why humans think and behave as they do. This award-winning twelve-volume reference covers every aspect of the ever-fascinating discipline of psychology and represents the most current knowledge in the field. This ten-year revision now covers discoveries based in neuroscience, clinical psychology's new interest in evidence-based practice and mindfulness, and new findings in social, developmental, and forensic psychology.

Handbook of Inorganic Qualitative Analysis

Handbook of Inorganic Qualitative Analysis PDF Author: Maharudra Chakraborty
Publisher: Independently Published
ISBN: 9781096649182
Category :
Languages : en
Pages : 60

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Book Description
This book is intended for undergraduate and postgraduate students in colleges and universities. Qualitative analysis in their inorganic chemistry practical courses plays a vital role to grow some knowledge in this field. However, most of the students feel difficulties during the detection of ions in inorganic salt mixtures because some ions in that mixture of salts interfere with the typical reactions of other ions.This book includes a systematic approach for the detection of inorganic acid and basic radicals when they are mixed together, even if the mixtures include more than six ions. Most of the difficulties and their removals have been given in this book so that student can easily report all the ions in their practical exam. Moreover, some special method for detection for a few complicated radicals is also included.For the postgraduate students, detections of some rare elements are also discussed.Hopefully, this book can be very much helpful to students and also to teachers of degree colleges and universities globally.I am very much thankful to my teachers for their teachings, otherwise, this book could not be successful.1. Colors of Inorganic Salts2. General Solubility of Inorganic Samples3. Scheme for Inorganic Qualitative Analysis4. Special Notes on Mixtures of Ions5. Difficulties and Their Removals During Group Analysis6. Addition of Some Common Reagents in Water Extract7. Detection of Rare Elements