Econometrics and economic statistics Books
Taylor & Francis Ltd Understanding Regression Analysis
Book SynopsisUnderstanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella -- namely, the conditional distribution model. It explains why the conditional distribution model is the correct model, and it also explains (proves) why the assumptions of the classical regression model are wrong. Unlike other regression books, this one from the outset takes a realistic approach that all models are just approximations. Hence, the emphasis is to model Nature's processes realistically, rather than to assume (incorrectly) that Nature works in particular, constrained ways.Key features of the book include: Numerous worked examples using the R software Key points and self-study questions displayed just-in-time within chapters <Trade Review"...The authors suggest their book is suitable for those who are “research-oriented”, regardless of any prior advanced training in statistics...I particularly like the emphasis on assumptions. Rather than discuss regression in idealized terms, Westfall and Arias are upfront about why assumptions are often wrong in practice, and what an analyst can do about violations. These discussions are woven into many of the chapters, and in some cases, they are featured in stand-alone chapters...I am a fan of learning statistics by doing, so the large amount of R code woven into the book’s chapters and the hands-on exercises at the end of each chapter are valuable and a welcomed feature of the book...To me, this textbook would be most suitable for a one-semester survey course in statistical methods for students outside of biostatistics or statistics. A motivated student could even use this book for self-study...Overall, I believe this is a worthwhile addition to the literature."- Ryan Andrews, ISCB News, June 2021 Table of Contents1. Introduction to Regression Models 2. Estimating Regression Model Parameters3. The Classical Model and Its Consequences4. Evaluating Assumptions5. Transformations6. The Multiple Regression Model7. Multiple Regression from the Matrix Point of View8. R-squared, Adjusted R-Squared, the F Test, and Multicollinearity9. Polynomial Models and Interaction (Moderator) Analysis10. ANOVA, ANCOVA, and Other Applications of Indicator Variables11. Variable Selection12. Heteroscedasticity and Non-independence13. Models for Binary, Nominal, and Ordinal Response Variables14. Models for Poisson and Negative Binomial Response15. Censored Data Models16. Outliers, Identification, Problems, and Remedies (Good and Bad)17. Neural Network Regression 18. Regression Trees19. Bookend
£39.99
Taylor & Francis Ltd Introduction to Time Series Modeling with Applications in R
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Taylor & Francis Ltd Oil and Gas Processing Equipment
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Taylor & Francis Ltd Models for Dependent Time Series
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£47.49
Taylor & Francis Ltd StateSpace Methods for Time Series Analysis
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Taylor & Francis Ltd Optimal Decision Making in Operations Research
Book SynopsisThe book provides insights in the decision-making for implementing strategies in various spheres of real-world issues. It integrates optimal policies in various decisionmaking problems and serves as a reference for researchers and industrial practitioners. Furthermore, the book provides sound knowledge of modelling of real-world problems and solution procedure using the various optimisation and statistical techniques for making optimal decisions. The book is meant for teachers, students, researchers and industrialists who are working in the field of materials science, especially operations research and applied statistics. Table of Contents1. A New Version of the Generalized Rayleigh Distribution with Copula, Properties, Applications and Different Methods of Estimation 2. Expanding the Burr X Model: Properties, Copula, Real Data Modeling and Different Methods of Estimation 3. Transmuted Burr Type X Model with Applications to Life Time Data 4. Monitoring Patients Blood Level through Enhanced Control Chart 5. Goodness of Fit in Parametric and Non-parametric Econometric Models 6. Stochastic Models for Cancer Progression and its Optimal Programming for Control with Chemotherapy 7. A New Unrelated Question Model with Two Questions Per Card 8. Hybrid of Simple Model and a New Unrelated Question Model for Two Sensitive Characteristics 9. Hybrid of Crossed Model and a New Unrelated Question Model for Two Sensitive Characteristics 10. Modified Regression Type Estimator by Ingeniously Utilizing Probabilities for more Efficient Results in Randomized Response Sampling 11. Ratio and Regression Type Estimators for a New Measure of Coefficient of Dispersion Relative to the Empirical Mode 12. Class of Exponential Ratio Type Estimator for Population Mean in Adaptive Cluster Sampling 13. An Inventory Model for Substitutable Deteriorating Products under Fuzzy and Cloud Fuzzy Demand Rate 14. Co-ordinated Selling Price and Replenishment Policies for Duopoly Retailers under Quadratic Demand and Deteriorating Nature of Items15. Quadratic Programming Approach for the Optimal Multi-objective Transportation Problem 16. Analyzing Multi-Objective Fixed-Charge Solid Transportation Problem under Rough and Fuzzy-Rough Environments 17. Overall Shale Gas Water Management: A Neutrosophic Optimization Approach 18. Memory Effect on an EOQ Model with Price Dependant Demand and Deterioration 19. Optimality Conditions of an Unconstrained Imprecise Optimization Problem via Interval Order Relation 20. Power Comparison of Different Goodness of Fit Tests for Beta Generalized Weibull Distribution 21. On the Transmuted Modified Lindley Distribution: Theory and Applications to Lifetime Data 22. Adjusted Bias and Risk for Estimating Treatment Effect after Selection with an Application in Idiopathic Osteoporosis 23. Validity Judgement of an EOQ Model using Phi-coefficient 24. Uncertain Chance-Constrained Multi-Objective Geometric Programming Problem 25. Optimal Decision Making for the Prediction of Diabetic Retinopathy in Type 2 Diabetes Mellitus Patients
£49.39
Taylor & Francis A StepbyStep Guide to Exploratory Factor Analysis
Book SynopsisThis is a concise, easy to use, step-by-step guide for applied researchers conducting exploratory factor analysis (EFA) using the open source software R. In this book, Dr. Watkins systematically reviews each decision step in EFA with screen shots of R and RStudio code, and recommends evidence-based best practice procedures. This is an eminently applied, practical approach with few or no formulas and is aimed at readers with little to no mathematical background. Dr. Watkins maintains an accessible tone throughout and uses minimal jargon and formula to help facilitate grasp of the key issues users will face while applying EFA, along with how to implement, interpret, and report results. Copious scholarly references and quotations are included to support the reader in responding to editorial reviews. This is a valuable resource for upper-level undergraduate and postgraduate students, as well as for more experienced researchers undertaking multivariate or structure equation modeling courses across the behavioral, medical, and social sciences.Trade Review"This book is an important contribution to the field. I have been publishing articles using EFA for over 30 years, yet it provided me with new insights and information on EFA. More importantly, the material is easy to follow and accessible to researchers and graduate students new to EFA. I highly recommend it to anyone seeking to become competent in EFA." – Joseph J. Glutting, Ph.D. University of Delaware, USA"A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio is an important contribution to the applied exploratory factor analytic literature. It is extremely well-written and portends to be a useful resource to researchers and students alike. It does a commendable job of describing how to implement exploratory factor analysis using R. I highly recommend this book." – Stefan C. Dombrowski, Ph.D. Rider University, USA"This book is an amazing resource for those new to factor analysis as well as those who have used it for some time. It is a terrific guide to best practices in exploratory factor analysis with rich explanations and descriptions for why various procedures are used and equally terrific in providing resources and guidance for using R for conducting factor analysis. I highly recommend this book." – Gary L. Canivez, Ph.D. Eastern Illinois University, USATable of ContentsPreface 1. Introduction 2. Data 3. R and RStudio Software4. Importing and Saving Data and Results 5. Decision Steps in Exploratory Factor Analysis 6. Step 1: Variables to Include 7. Step 2: Participants 8. Step 3: Data Screening 9. Step 4: Is Exploratory Factor Analysis Appropriate10. Step 5: Factor Analysis Model 11. Step 6: Factor Extraction Method 12. Step 7: How Many Factors to Retain 13. Step 8: Rotate Factors 14. Step 9: Interpret Exploratory Factor Analysis Results 15. Step 10: Report Exploratory Factor Analysis Results 16. Exploratory Factor Analysis with Categorical Variables17. Higher-order and Bifactor Models 18. Exploratory Versus Confirmatory Factor AnalysisPractice ExercisesReferences and resources
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Taylor & Francis Ltd Machine Learning for Factor Investing
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Taylor & Francis Ltd Protecting Your Privacy in a DataDriven World
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Taylor & Francis Ltd Protecting Your Privacy in a DataDriven World
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Taylor & Francis Ltd Introduction to Econophysics
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Taylor & Francis Ltd Introduction to Statistical Methods for Financial Models
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Taylor & Francis The History of Money and Monetary Arrangements
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Taylor & Francis A New Measure of Competition in the Financial Industry
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Taylor & Francis Ltd Gini Inequality Index
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Taylor & Francis Categorical and Nonparametric Data Analysis
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Taylor & Francis Ltd ANOVA and Mixed Models
ANOVA and Mixed Models: A Short Introduction Using R provides both the practitioner and researcher a compact introduction to the analysis of data from the most popular experimental designs. Based on knowledge from an introductory course on probability and statistics, the theoretical foundations of the most important models are introduced. The focus is on an intuitive understanding of the theory, common pitfalls in practice, and the application of the methods in R. From data visualization and model fitting, up to the interpretation of the corresponding output, the whole workflow is presented using R. The book does not only cover standard ANOVA models, but also models for more advanced designs and mixed models, which are common in many practical applications.Features Accessible to readers with a basic background in probability and statistics Covers fundamental concepts of experimen
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Taylor & Francis Ltd ANOVA and Mixed Models
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Taylor & Francis A StepbyStep Guide to Exploratory Factor Analysis with SPSS
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Taylor & Francis Ltd An Introduction to Computational Risk Management of EquityLinked Insurance Chapman and HallCRC Financial Mathematics
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Taylor & Francis Ltd Design Analysis of Clinical Trials for Economic Evaluation Reimbursement
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Taylor & Francis Ltd Risk Measures and Insurance Solvency Benchmarks
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Taylor & Francis Ltd Linear Regression Models
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Taylor & Francis Ltd Linear Regression Models
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Taylor & Francis Applied Structural Equation Modeling using AMOS Basic to Advanced Techniques
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Taylor & Francis Qualitative Methods in Economics
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Taylor & Francis Ltd Probability Foundations of Economic Theory
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Taylor & Francis Trade Theory and Econometrics
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Taylor & Francis Ltd The Development of Economics in Western Europe Since 1945
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Taylor & Francis Ltd Financial Econometrics
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Taylor & Francis Empirical Models and Policy Making Interaction and Institutions
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Taylor & Francis Econometric Analysis of the Real Estate Market and Investment
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Taylor & Francis Policy Evaluation with Computable General Equilibrium Models
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Taylor & Francis Dynamic Economic Models in Discrete Time Theory and Empirical Applications
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Taylor & Francis The Economics of Search
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Taylor & Francis Ltd Family Time The Social Organization of Care 2 Routledge IAFFE Advances in Feminist Economics
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Taylor & Francis Formula Funding of Public Services
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Taylor & Francis Race and Economic Opportunity in the TwentyFirst Century 90 Routledge Frontiers of Political Economy
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Taylor & Francis Advanced Statistics for Kinesiology and Exercise Science
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Taylor & Francis Advanced Statistics for Kinesiology and Exercise Science
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Taylor & Francis Information Economics Routledge Advanced Texts in Economics and Finance
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Taylor & Francis The Singapore Economy
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Taylor & Francis The Years of High Econometrics
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Taylor & Francis Ltd Financial Econometrics Routledge Advanced Texts in Economics and Finance
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Taylor & Francis Ltd Financial Econometrics Routledge Advanced Texts in Economics and Finance
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Taylor & Francis Ltd Advances on Income Inequality and Concentration Measures
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Taylor & Francis The Analysis of Linear Economic Systems Father Maurice Potrons Pioneering Works 117 Routledge Studies in the History of Economics
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Taylor & Francis Formula Funding of Public Services
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