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Philosophy --- Knowledge, Theory of. --- Inference. --- Thought and thinking.

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When people speak, their words never fully encode what they mean, and the context is always compatible with a variety of interpretations. How can comprehension ever be achieved? Wilson and Sperber argue that comprehension is a process of inference guided by precise expectations of relevance. What are the relations between the linguistically encoded meanings studied in semantics and the thoughts that humans are capable of entertaining and conveying? How should we analyse literal meaning, approximations, metaphors and ironies? Is the ability to understand speakers' meanings rooted in a more general human ability to understand other minds? How do these abilities interact in evolution and in cognitive development? Meaning and Relevance sets out to answer these and other questions, enriching and updating relevance theory and exploring its implications for linguistics, philosophy, cognitive science and literary studies.

Lexicology. Semantics --- Psycholinguistics --- Semantics --- Relevance (Philosophy) --- Inference --- Cognition --- Sémantique --- Pertinence (Logique) --- Inférence (Logique) --- Semantics. --- Relevance. --- Inference. --- Cognition. --- 801.56 --- Syntaxis. Semantiek --- 801.56 Syntaxis. Semantiek --- Sémantique --- Inférence (Logique) --- Relevance --- Formal semantics --- Semasiology --- Semiology (Semantics) --- Comparative linguistics --- Information theory --- Language and languages --- Lexicology --- Meaning (Psychology) --- Pertinence --- Relevancy --- Meaning (Philosophy) --- Ampliative induction --- Induction, Ampliative --- Inference (Logic) --- Reasoning --- Psychology --- Arts and Humanities --- Language & Linguistics --- Inférence --- Théorie de la pertinence (linguistique) --- Inférence --- Théorie de la pertinence (linguistique)

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This book provides a quick but insightful introduction to Bayesian tracking and particle filtering for a person who has some background in probability and statistics and wishes to learn the basics of single-target tracking. It also introduces the reader to multiple target tracking by presenting useful approximate methods that are easy to implement compared to full-blown multiple target trackers. The book presents the basic concepts of Bayesian inference and demonstrates the power of the Bayesian method through numerous applications of particle filters to tracking and smoothing problems. It emphasizes target motion models that incorporate knowledge about the target’s behavior in a natural fashion rather than assumptions made for mathematical convenience. The background provided by this book allows a person to quickly become a productive member of a project team using Bayesian filtering and to develop new methods and techniques for problems the team may face.

Statistical science --- Mathematical statistics --- Information systems --- statistiek --- gegevensanalyse --- Engineering—Data processing. --- Statistics. --- Big data. --- Data Engineering. --- Bayesian Inference. --- Big Data. --- Mathematics

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Decision theory and the theory of rational choice have recently been the subjects of considerable research by philosophers and economists. However, no adequate anthology exists which can be used to introduce students to the field. This volume is designed to meet that need. The essays included are organized into five parts covering the foundations of decision theory, the conceptualization of probability and utility, pholosophical difficulties with the rules of rationality and with the assessment of probability, and causal decision theory. The editors provide an extensive introduction to the field and introductions to each part.

Mathematical statistics --- 519.226 --- Bayesian statistical decision theory. --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Inference and decision theory. Likelihood. Bayesian theory. Fiducial probability --- 519.226 Inference and decision theory. Likelihood. Bayesian theory. Fiducial probability --- Bayesian statistical decision theory --- Arts and Humanities --- Philosophy

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This textbook reconstructs the statistics curriculum from the perspective of posterior probability. In recent years, there have been several reports that the results of studies using significant tests cannot be reproduced. It is a problem called a “reproducibility crisis”. For example, suppose we could reject the null hypothesis that “the average number of days to recovery in patients who took a new drug was the same as that in the control group”. However, rejecting the null hypothesis is only a necessary condition for the new drug to be effective. Even if the necessary conditions are met, it does not necessarily mean that the new drug is effective. In fact, there are many cases where the effect is not reproduced. Sufficient conditions should be presented, such as “the average number of days until recovery in patients who take new drugs is sufficiently short compared to the control group, evaluated from a medical point of view”, without paying attention to necessary conditions. This book reconstructs statistics from the perspective of PHC, i.e., probability that a research hypothesis is correct. For example, the PHC curve shows the posterior probability that the statement “The average number of days until recovery for patients taking a new drug is at least θ days shorter than that of the control group” is correct as a function of θ. Using the PHC curve makes it possible to discuss the sufficient conditions rather than the necessary conditions for being an efficient treatment. The value of statistical research should be evaluated with concrete indicators such as “90% probability of being at least 3 days shorter”, not abstract metrics like the p-value.

Psychology --- Social sciences (general) --- Statistical science --- Mathematical statistics --- Probability theory --- waarschijnlijkheidstheorie --- psychologie --- sociale wetenschappen --- statistiek --- statistisch onderzoek --- Social sciences --- Statistics. --- Markov processes. --- Mathematical statistics. --- Psychometrics. --- Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy. --- Statistical Theory and Methods. --- Markov Process. --- Bayesian Inference. --- Parametric Inference. --- Statistical methods. --- Estadística matemàtica --- Probabilitats