Download or read book Reasoning with Qualitative Linear Models written by Renato De Mori and published by . This book was released on 1990 with total page 39 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some applications of discrepancy analysis are suggested. Qualitative linear models (QLMs) are introduced as qualitative versions of systems of first-order, linear differential equations. All variables, including signals, are represented by qualitative interval labels (QILs), which combine the advantages of discrete sets of labels and interval labels. A form of qualitative reasoning, based on perturbations to labels and constraint satisfaction, is proposed and analysed."
Download or read book Qualitative Reasoning written by Hannes Werthner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a survey about the field of Qualitative Reasoning, it contrasts and classifies its approaches and puts them into a common framework. Qualitative Reasoning represents an approach of Artificial Intelligence to model dynamic systems, about which little information is available, and to derive statements about the potential behavior of these systems, putting emphasis on a causal explanation of the behavior. Both variables and relationships between variables are described by means of qualitative terms such as small and large or positive and negative. Since this approach also takes into consideration the way how humans reason about physical systems, it can be stated that Qualitative Reasoning participates in the creation of a cognitive theory of non-numerical process descriptions which can be mapped onto a digital computer. This approach can be used for simulation, diagnosis, design, structure identification and interpretation. Areas of application are physics, medicine, the field of ecology, process control, etc. In addition to the classification of existing methods, the book presents a new approach based on fuzzy sets. And the work relates Qualitative Reasoning with such fields of Expert Systems, System Theory and Cognitive Science.
Download or read book Analyzing Qualitative categorical Data written by Leo A. Goodman and published by . This book was released on 1978 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: The logit model; The general log-linear model; Davis on Goodman's approach; Latent structure and scaling models; Some extensions to the goodman system.
Download or read book The Illusion of Linearity written by Dirk de Bock and published by Springer Science & Business Media. This book was released on 2007-09-30 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the reader with a comprehensive overview of the major findings of the recent research on the illusion of linearity. It discusses: how the illusion of linearity appears in diverse domains of mathematics and science; what are the crucial psychological, mathematical, and educational factors being responsible for the occurrence and persistence of the phenomenon; and how the illusion of linearity can be remedied.
Download or read book Qualitative Simulation Modeling and Analysis written by Paul A. Fishwick and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently there has been considerable interest in qualitative methods in simulation and mathematical model- ing. Qualitative Simulation Modeling and Analysis is the first book to thoroughly review fundamental concepts in the field of qualitative simulation. The book will appeal to readers in a variety of disciplines including researchers in simulation methodology, artificial intelligence and engineering. This book boldly attempts to bring together, for the first time, the qualitative techniques previously found only in hard-to-find journals dedicated to single disciplines. The book is written for scientists and engineers interested in improving their knowledge of simulation modeling. The "qualitative" nature of the book stresses concepts of invariance, uncertainty and graph-theoretic bases for modeling and analysis.
Download or read book Qualitative Reasoning in the Automated Categorization of Linear Viscoelastic Models written by Syed Malek Fakar Duani bin Syed Mustapha and published by . This book was released on 1997 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Generalized Linear Models for Bounded and Limited Quantitative Variables written by Michael Smithson and published by SAGE Publications. This book was released on 2019-09-09 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces researchers and students to the concepts and generalized linear models for analyzing quantitative random variables that have one or more bounds. Examples of bounded variables include the percentage of a population eligible to vote (bounded from 0 to 100), or reaction time in milliseconds (bounded below by 0). The human sciences deal in many variables that are bounded. Ignoring bounds can result in misestimation and improper statistical inference. Michael Smithson and Yiyun Shou′s book brings together material on the analysis of limited and bounded variables that is scattered across the literature in several disciplines, and presents it in a style that is both more accessible and up-to-date. The authors provide worked examples in each chapter using real datasets from a variety of disciplines. The software used for the examples include R, SAS, and Stata. The data, software code, and detailed explanations of the example models are available on an accompanying website.
Download or read book Logical and Computational Aspects of Model Based Reasoning written by L. Magnani and published by Springer Science & Business Media. This book was released on 2002-09-30 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information technology has been, in recent years, under increasing commercial pressure to provide devices and systems which help/ replace the human in his daily activity. This pressure requires the use of logic as the underlying foundational workhorse of the area. New logics were developed as the need arose and new foci and balance has evolved within logic itself. One aspect of these new trends in logic is the rising impor tance of model based reasoning. Logics have become more and more tailored to applications and their reasoning has become more and more application dependent. In fact, some years ago, I myself coined the phrase "direct deductive reasoning in application areas", advocating the methodology of model-based reasoning in the strongest possible terms. Certainly my discipline of Labelled Deductive Systems allows to bring "pieces" of the application areas as "labels" into the logic. I therefore heartily welcome this important book to Volume 25 of the Applied Logic Series and see it as an important contribution in our overall coverage of applied logic.
Download or read book Linear Models with R written by Julian J. Faraway and published by Chapman and Hall/CRC. This book was released on 2004-08-12 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Books on regression and the analysis of variance abound—many are introductory, many are theoretical. While most of them do serve a purpose, the fact remains that data analysis cannot be properly learned without actually doing it, and this means using a statistical software package. There are many of these to choose from, all with their particular strengths and weaknesses. Lately, however, one such package has begun to rise above the others thanks to its free availability, its versatility as a programming language, and its interactivity. That software is R. In the first book that directly uses R to teach data analysis, Linear Models with R focuses on the practice of regression and analysis of variance. It clearly demonstrates the different methods available and, more importantly, in which situations each one applies. It covers all of the standard topics, from the basics of estimation to missing data, factorial designs, and block designs. It also discusses topics, such as model uncertainty, rarely addressed in books of this type. The presentation incorporates numerous examples that clarify both the use of each technique and the conclusions one can draw from the results. All of the data sets used in the book are available for download from http://people.bath.ac.uk/jjf23/LMR/ The author assumes that readers know the essentials of statistical inference and have a basic knowledge of data analysis, linear algebra, and calculus. The treatment reflects his view of statistical theory and his belief that qualitative statistical concepts, while somewhat more difficult to learn, are just as important because they enable us to practice statistics rather than just talk about it.
Download or read book Readings in Qualitative Reasoning about Physical Systems written by Daniel S. Weld and published by Morgan Kaufmann Publishers. This book was released on 1990 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ability to reason qualitatively about physical systems is important to understanding and interacting with the world for both humans and intelligent machines. Accordingly, this study has become an important subject of research in the artificial intelligence and cognitive science communities. The goal of "qualitative physics," as the field is sometimes known, is to capture both the commonsense knowledge of the person on the street and the tacit knowledge underlying the quantitative knowledge used by engineers and scientists. "Readings in Qualitative Reasoning About Physical Systems" is an introduction and source book for this dynamic area, presenting reprints of key papers chosen by the editors and a group of expert referees. The editors present introductions discussing the context and significance of each group of articles as well as providing pointers to the rest of the literature. In addition, the volume includes several original papers that are not available elsewhere.
Download or read book Linear Models in Matrix Form written by Jonathon D. Brown and published by Springer. This book was released on 2016-10-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is an approachable introduction to statistical analysis using matrix algebra. Prior knowledge of matrix algebra is not necessary. Advanced topics are easy to follow through analyses that were performed on an open-source spreadsheet using a few built-in functions. These topics include ordinary linear regression, as well as maximum likelihood estimation, matrix decompositions, nonparametric smoothers and penalized cubic splines. Each data set (1) contains a limited number of observations to encourage readers to do the calculations themselves, and (2) tells a coherent story based on statistical significance and confidence intervals. In this way, students will learn how the numbers were generated and how they can be used to make cogent arguments about everyday matters. This textbook is designed for use in upper level undergraduate courses or first year graduate courses. The first chapter introduces students to linear equations, then covers matrix algebra, focusing on three essential operations: sum of squares, the determinant, and the inverse. These operations are explained in everyday language, and their calculations are demonstrated using concrete examples. The remaining chapters build on these operations, progressing from simple linear regression to mediational models with bootstrapped standard errors.
Download or read book Regression Linear Modeling written by Jason W. Osborne and published by SAGE Publications. This book was released on 2016-03-24 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a conversational tone, Regression & Linear Modeling provides conceptual, user-friendly coverage of the generalized linear model (GLM). Readers will become familiar with applications of ordinary least squares (OLS) regression, binary and multinomial logistic regression, ordinal regression, Poisson regression, and loglinear models. The author returns to certain themes throughout the text, such as testing assumptions, examining data quality, and, where appropriate, nonlinear and non-additive effects modeled within different types of linear models.
Download or read book An Introduction to Generalized Linear Models written by George H. Dunteman and published by SAGE Publications. This book was released on 2005-09-22 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you have data that is not normally distributed and don′t know how to analyze it using generalized linear models (GLM)? Beginning with a discussion of fundamental statistical modeling concepts in a multiple regression framework, the authors extend these concepts to GLM (including Poisson regression. logistic regression, and proportional hazards models) and demonstrate the similarity of various regression models to GLM. Each procedure is illustrated using real life data sets, and the computer instructions and results will be presented for each example. Throughout the book, there is an emphasis on link functions and error distribution and how the model specifications translate into likelihood functions that can, through maximum likelihood estimation be used to estimate the regression parameters and their associated standard errors. This book provides readers with basic modeling principles that are applicable to a wide variety of situations. Key Features: - Provides an accessible but thorough introduction to GLM, exponential family distribution, and maximum likelihood estimation - Includes discussion on checking model adequacy and description on how to use SAS to fit GLM - Describes the connection between survival analysis and GLM This book is an ideal text for social science researchers who do not have a strong statistical background, but would like to learn more advanced techniques having taken an introductory course covering regression analysis.
Download or read book Interpreting Quantitative Data written by David Byrne and published by SAGE. This book was released on 2002-04-11 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: How do quantitative methods help us to acquire knowledge of the real world? What are the `do's' and `don'ts' of effective quantitative research? This refreshing and accessible book provides students with a novel and useful resource for doing quantitative research. It offers students a guide on how to: interpret the complex reality of the social world; achieve effective measurement; understand the use of official statistics; use social surveys; understand probability and quantitative reasoning; interpret measurements; apply linear modelling; understand simulation and neural nets; and integrate quantitative and qualitative modelling in the research process. Jargon-free and written with the needs of students in mind, the book will be required reading for students interested in using quantitative research methods.
Download or read book A Set Theoretic Foundation of Qualitative Reasoning and its Application to the Modeling of Economics and Business Management Problems written by Karl Reiner Lang and published by . This book was released on 2008 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: The qualitative reasoning (QR) field has developed various representation and reasoning methods for the modeling with incomplete information or incomplete knowledge. While most uncertain reasoning approaches describe uncertain or imprecisely known information as probability distribution functions, qualitative reasoning bases its model specification on qualitative descriptions that are derived from known qualitative system properties. Problems are formulated as sets of qualitative constraints and their analysis is performed by applying a qualitative calculus. This paper presents a general, unifying theory of the various existing qualitative reasoning systems that includes, as special cases, reasoning methods that use representations of qualitative differential equations and qualitative difference equations. Based on set theory, our QR framework describes fundamental concepts such as qualitative models and solutions, and relates them to the quantitative analogues of its underlying quantitative reference system. Our motivation arises from the types of models found in the management sciences. Thus we emphasize the significance of discrete, dynamic models and optimization models in the business management and economics fields, both of which have received less attention in current QR research. Finally, we extend our theoretical framework to include an approach to qualitative optimization.
Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Download or read book Readings in Qualitative Reasoning About Physical Systems written by Daniel S. Weld and published by Morgan Kaufmann. This book was released on 2013-09-17 with total page 733 pages. Available in PDF, EPUB and Kindle. Book excerpt: Readings in Qualitative Reasoning about Physical Systems describes the automated reasoning about the physical world using qualitative representations. This text is divided into nine chapters, each focusing on some aspect of qualitative physics. The first chapter deal with qualitative physics, which is concerned with representing and reasoning about the physical world. The goal of qualitative physics is to capture both the commonsense knowledge of the person on the street and the tacit knowledge underlying the quantitative knowledge used by engineers and scientists. The succeeding chapter discusses the qualitative calculus and its role in constructing an envisionment that includes behavior over both mythical time and elapsed time. These topics are followed by reviews of the mathematical aspects of qualitative reasoning, history-based simulation and temporal reasoning, as well as the intelligence in scientific computing. The final chapters are devoted to automated modeling for qualitative reasoning and causal explanations of behavior. These chapters also examine the qualitative kinematics of reasoning about shape and space. This book will prove useful to psychologists and psychiatrists.
