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Choosing Models of Society and Social Norms

Choosing Models of Society and Social Norms PDF Author: Adolfo Critto
Publisher: University Press of America
ISBN: 9780761814542
Category : Philosophy
Languages : en
Pages : 370

Book Description
Choosing Models of Society and Social Norms offers an innovative approach to social norms and decision-making that encourages the identification of social norms, along with their causes and consequences. Adolfo Critto points out that social norms condition behavior, but are also conditioned by human decisions. He notes that social norms generally only provide partial and temporary solutions to human needs and problems, so must be critically analyzed in order to understand their relationship to decision making. Critto approaches this relationship through "sacred" (focused on transcendent ends) and "expedient" (focused on efficient means) value orientations, warning that a one-sided focus on either of these orientations leads to inconsistency. He stresses the importance of language, communication, and education, showing how they relate to social norms. Through his analysis, the author provides an understanding of the creation of social norms, what influences them, and the evaluation of those that already exist.

Choosing Models of Society and Social Norms

Choosing Models of Society and Social Norms PDF Author: Adolfo Critto
Publisher: University Press of America
ISBN: 9780761814542
Category : Philosophy
Languages : en
Pages : 370

Book Description
Choosing Models of Society and Social Norms offers an innovative approach to social norms and decision-making that encourages the identification of social norms, along with their causes and consequences. Adolfo Critto points out that social norms condition behavior, but are also conditioned by human decisions. He notes that social norms generally only provide partial and temporary solutions to human needs and problems, so must be critically analyzed in order to understand their relationship to decision making. Critto approaches this relationship through "sacred" (focused on transcendent ends) and "expedient" (focused on efficient means) value orientations, warning that a one-sided focus on either of these orientations leads to inconsistency. He stresses the importance of language, communication, and education, showing how they relate to social norms. Through his analysis, the author provides an understanding of the creation of social norms, what influences them, and the evaluation of those that already exist.

Choosing a Career as a Model

Choosing a Career as a Model PDF Author: Cheryl Tobey
Publisher: The Rosen Publishing Group, Inc
ISBN: 9780823932436
Category : Juvenile Nonfiction
Languages : en
Pages : 68

Book Description
Introduces various careers in the field of modeling, including fashion, commercial, and specialized opportunities.

Model Selection and Model Averaging

Model Selection and Model Averaging PDF Author: Gerda Claeskens
Publisher: Cambridge University Press
ISBN: 1139471805
Category : Mathematics
Languages : en
Pages : 312

Book Description
Given a data set, you can fit thousands of models at the push of a button, but how do you choose the best? With so many candidate models, overfitting is a real danger. Is the monkey who typed Hamlet actually a good writer? Choosing a model is central to all statistical work with data. We have seen rapid advances in model fitting and in the theoretical understanding of model selection, yet this book is the first to synthesize research and practice from this active field. Model choice criteria are explained, discussed and compared, including the AIC, BIC, DIC and FIC. The uncertainties involved with model selection are tackled, with discussions of frequentist and Bayesian methods; model averaging schemes are presented. Real-data examples are complemented by derivations providing deeper insight into the methodology, and instructive exercises build familiarity with the methods. The companion website features Data sets and R code.

Feature Engineering and Selection

Feature Engineering and Selection PDF Author: Max Kuhn
Publisher: CRC Press
ISBN: 1351609467
Category : Business & Economics
Languages : en
Pages : 266

Book Description
The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Model Selection and Inference

Model Selection and Inference PDF Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
ISBN: 1475729170
Category : Mathematics
Languages : en
Pages : 373

Book Description
Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.

Model Selection and Multimodel Inference

Model Selection and Multimodel Inference PDF Author: Kenneth P. Burnham
Publisher: Springer Science & Business Media
ISBN: 0387224564
Category : Mathematics
Languages : en
Pages : 512

Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

Optimal Design of Experiments

Optimal Design of Experiments PDF Author: Peter Goos
Publisher: John Wiley & Sons
ISBN: 1119976162
Category : Science
Languages : en
Pages : 249

Book Description
"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.

Estimating and Choosing

Estimating and Choosing PDF Author: Georges Matheron
Publisher: Springer Science & Business Media
ISBN: 364248817X
Category : Technology & Engineering
Languages : en
Pages : 147

Book Description
Ever since the beginning of modern probability theory in the seventeenth century there has been a continuous debate over the meaning and applicability of the concept of probability. This book presents a coherent and well thoughtout framework for the use of probabilistic models to describe unique phenomena in a purely objective way. Although Estimating and Choosing was written with geostatistical applications in mind, the approach is of general applicability across the whole spectrum of probabilistic modelling. The only full-fledged treatment of the foundations of practical probability modelling ever written, this book fills an important gap in the literature of probability and statistics.

Regression and Time Series Model Selection

Regression and Time Series Model Selection PDF Author: Allan D. R. McQuarrie
Publisher: World Scientific
ISBN: 9812385452
Category : Mathematics
Languages : en
Pages : 479

Book Description
This important book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. The book also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models.

Machine Learning and Data Science Blueprints for Finance

Machine Learning and Data Science Blueprints for Finance PDF Author: Hariom Tatsat
Publisher: "O'Reilly Media, Inc."
ISBN: 1492073008
Category : Computers
Languages : en
Pages : 432

Book Description
Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You’ll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations