Eliciting Subjective Probabilities with Binary Lotteries

DEFF Research Database (Denmark)

Harrison, Glenn W.; Martínez-Correa, Jimmy; Swarthout, J. Todd

objective probabilities. Drawing a sample from the same subject population, we find evidence that the binary lottery procedure induces linear utility in a subjective probability elicitation task using the Quadratic Scoring Rule. We also show that the binary lottery procedure can induce direct revelation...

Approximation methods in probability theory

CERN Document Server

Čekanavičius, Vydas

2016-01-01

This book presents a wide range of well-known and less common methods used for estimating the accuracy of probabilistic approximations, including the Esseen type inversion formulas, the Stein method as well as the methods of convolutions and triangle function. Emphasising the correct usage of the methods presented, each step required for the proofs is examined in detail. As a result, this textbook provides valuable tools for proving approximation theorems. While Approximation Methods in Probability Theory will appeal to everyone interested in limit theorems of probability theory, the book is particularly aimed at graduate students who have completed a standard intermediate course in probability theory. Furthermore, experienced researchers wanting to enlarge their toolkit will also find this book useful.

Probability theory and applications

CERN Document Server

Hsu, Elton P

1999-01-01

This volume, with contributions by leading experts in the field, is a collection of lecture notes of the six minicourses given at the IAS/Park City Summer Mathematics Institute. It introduces advanced graduates and researchers in probability theory to several of the currently active research areas in the field. Each course is self-contained with references and contains basic materials and recent results. Topics include interacting particle systems, percolation theory, analysis on path and loop spaces, and mathematical finance. The volume gives a balanced overview of the current status of probability theory. An extensive bibliography for further study and research is included. This unique collection presents several important areas of current research and a valuable survey reflecting the diversity of the field.

Subjective Expected Utility Theory without States of the World

OpenAIRE

Edi Karni

2005-01-01

This paper develops an axiomatic theory of decision making under uncertainty that dispenses with the state space. The results are subjective expected utility models with unique, action-dependent, subjective probabilities, and a utility function defined over wealth-effect pairs that is unique up to positive linear transformation.

Excluding joint probabilities from quantum theory

Science.gov (United States)

Allahverdyan, Armen E.; Danageozian, Arshag

2018-03-01

Quantum theory does not provide a unique definition for the joint probability of two noncommuting observables, which is the next important question after the Born's probability for a single observable. Instead, various definitions were suggested, e.g., via quasiprobabilities or via hidden-variable theories. After reviewing open issues of the joint probability, we relate it to quantum imprecise probabilities, which are noncontextual and are consistent with all constraints expected from a quantum probability. We study two noncommuting observables in a two-dimensional Hilbert space and show that there is no precise joint probability that applies for any quantum state and is consistent with imprecise probabilities. This contrasts with theorems by Bell and Kochen-Specker that exclude joint probabilities for more than two noncommuting observables, in Hilbert space with dimension larger than two. If measurement contexts are included into the definition, joint probabilities are not excluded anymore, but they are still constrained by imprecise probabilities.

Probability theory and mathematical statistics for engineers

CERN Document Server

Pugachev, V S

1984-01-01

Probability Theory and Mathematical Statistics for Engineers focuses on the concepts of probability theory and mathematical statistics for finite-dimensional random variables.The publication first underscores the probabilities of events, random variables, and numerical characteristics of random variables. Discussions focus on canonical expansions of random vectors, second-order moments of random vectors, generalization of the density concept, entropy of a distribution, direct evaluation of probabilities, and conditional probabilities. The text then examines projections of random vector

Causal inference, probability theory, and graphical insights.

Science.gov (United States)

Baker, Stuart G

2013-11-10

Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design. Published 2013. This article is a US Government work and is in the public domain in the USA.

Handbook of probability theory and applications

CERN Document Server

Rudas, Tamas

2008-01-01

""This is a valuable reference guide for readers interested in gaining a basic understanding of probability theory or its applications in problem solving in the other disciplines.""-CHOICEProviding cutting-edge perspectives and real-world insights into the greater utility of probability and its applications, the Handbook of Probability offers an equal balance of theory and direct applications in a non-technical, yet comprehensive, format. Editor Tamás Rudas and the internationally-known contributors present the material in a manner so that researchers of vari

Probability, statistics, and queueing theory

CERN Document Server

Allen, Arnold O

1990-01-01

This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edit

Foundations of the theory of probability

CERN Document Server

Kolmogorov, AN

2018-01-01

This famous little book remains a foundational text for the understanding of probability theory, important both to students beginning a serious study of probability and to historians of modern mathematics. 1956 second edition.

Subjective Probabilities for State-Dependent Continuous Utility

NARCIS (Netherlands)

P.P. Wakker (Peter)

1987-01-01

textabstractFor the expected utility model with state dependent utilities, Karni, Schmeidler and Vind (1983) have shown how to recover uniquely the involved subjective probabilities if the preferences, contingent on a hypothetical probability distribution over the state space, are known. This they

Joseph L Doob and Development of Probability Theory

Indian Academy of Sciences (India)

IAS Admin

(equivalent to BSc in India) in mathematics at the famous Harvard University, ... Doob says that the force of economic circumstances got him into probability theory. ... Books. J L Doob established probability theory as a major discipline of study ...

Hamiltonian theories quantization based on a probability operator

International Nuclear Information System (INIS)

Entral'go, E.E.

1986-01-01

The quantization method with a linear reflection of classical coordinate-momentum-time functions Λ(q,p,t) at quantum operators in a space of quantum states ψ, is considered. The probability operator satisfies a system of equations representing the principles of dynamical and canonical correspondences between the classical and quantum theories. The quantization based on a probability operator leads to a quantum theory with a nonnegative joint coordinate-momentum distribution function for any state ψ. The main consequences of quantum mechanics with a probability operator are discussed in comparison with the generally accepted quantum and classical theories. It is shown that a probability operator leads to an appearance of some new notions called ''subquantum'' ones. Hence the quantum theory with a probability operator does not pretend to any complete description of physical reality in terms of classical variables and by this reason contains no problems like Einstein-Podolsky-Rosen paradox. The results of some concrete problems are given: a free particle, a harmonic oscillator, an electron in the Coulomb field. These results give hope on the possibility of an experimental verification of the quantization based on a probability operator

Independent events in elementary probability theory

Science.gov (United States)

Csenki, Attila

2011-07-01

In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): quote specific-use="indent"> If the n events E 1, E 2, … , E n are jointly independent then any two events A and B built in finitely many steps from two disjoint subsets of E 1, E 2, … , E n are also independent. The operations 'union', 'intersection' and 'complementation' are permitted only when forming the events A and B. quote>Here we examine this statement from the point of view of elementary probability theory. The approach described here is accessible also to users of probability theory and is believed to be novel.

Probability theory plus noise: Replies to Crupi and Tentori (2016) and to Nilsson, Juslin, and Winman (2016).

Science.gov (United States)

Costello, Fintan; Watts, Paul

2016-01-01

A standard assumption in much of current psychology is that people do not reason about probability using the rules of probability theory but instead use various heuristics or "rules of thumb," which can produce systematic reasoning biases. In Costello and Watts (2014), we showed that a number of these biases can be explained by a model where people reason according to probability theory but are subject to random noise. More importantly, that model also predicted agreement with probability theory for certain expressions that cancel the effects of random noise: Experimental results strongly confirmed this prediction, showing that probabilistic reasoning is simultaneously systematically biased and "surprisingly rational." In their commentaries on that paper, both Crupi and Tentori (2016) and Nilsson, Juslin, and Winman (2016) point to various experimental results that, they suggest, our model cannot explain. In this reply, we show that our probability theory plus noise model can in fact explain every one of the results identified by these authors. This gives a degree of additional support to the view that people's probability judgments embody the rational rules of probability theory and that biases in those judgments can be explained as simply effects of random noise. (c) 2015 APA, all rights reserved).

Introduction to probability and measure theories

International Nuclear Information System (INIS)

Partasarati, K.

1983-01-01

Chapters of probability and measured theories are presented. The Borele images of spaces with the measure into each other and in separate metric spaces are studied. The Kolmogorov theorem on the continuation of probabilies is drawn from the theorem on the measure continuation to the projective limits of spaces with measure. The integration theory is plotted, measures on multiplications of spaces are studied. The theory of conventional mathematical expectations by projections in Hilbert space is presented. In conclusion, the theory of weak convergence of measures of elements of the theory of characteristic functions and the theory of invariant and quasi-invariant measures on groups and homogeneous spaces is given

Paradoxes in probability theory

CERN Document Server

Eckhardt, William

2013-01-01

Paradoxes provide a vehicle for exposing misinterpretations and misapplications of accepted principles. This book discusses seven paradoxes surrounding probability theory.  Some remain the focus of controversy; others have allegedly been solved, however the accepted solutions are demonstrably incorrect. Each paradox is shown to rest on one or more fallacies.  Instead of the esoteric, idiosyncratic, and untested methods that have been brought to bear on these problems, the book invokes uncontroversial probability principles, acceptable both to frequentists and subjectivists. The philosophical disputation inspired by these paradoxes is shown to be misguided and unnecessary; for instance, startling claims concerning human destiny and the nature of reality are directly related to fallacious reasoning in a betting paradox, and a problem analyzed in philosophy journals is resolved by means of a computer program.

Probability Estimation in the Framework of Intuitionistic Fuzzy Evidence Theory

Directory of Open Access Journals (Sweden)

Yafei Song

2015-01-01

Full Text Available Intuitionistic fuzzy (IF evidence theory, as an extension of Dempster-Shafer theory of evidence to the intuitionistic fuzzy environment, is exploited to process imprecise and vague information. Since its inception, much interest has been concentrated on IF evidence theory. Many works on the belief functions in IF information systems have appeared. Although belief functions on the IF sets can deal with uncertainty and vagueness well, it is not convenient for decision making. This paper addresses the issue of probability estimation in the framework of IF evidence theory with the hope of making rational decision. Background knowledge about evidence theory, fuzzy set, and IF set is firstly reviewed, followed by introduction of IF evidence theory. Axiomatic properties of probability distribution are then proposed to assist our interpretation. Finally, probability estimations based on fuzzy and IF belief functions together with their proofs are presented. It is verified that the probability estimation method based on IF belief functions is also potentially applicable to classical evidence theory and fuzzy evidence theory. Moreover, IF belief functions can be combined in a convenient way once they are transformed to interval-valued possibilities.

Tests of Cumulative Prospect Theory with graphical displays of probability

Directory of Open Access Journals (Sweden)

Michael H. Birnbaum

2008-10-01

Full Text Available Recent research reported evidence that contradicts cumulative prospect theory and the priority heuristic. The same body of research also violates two editing principles of original prospect theory: cancellation (the principle that people delete any attribute that is the same in both alternatives before deciding between them and combination (the principle that people combine branches leading to the same consequence by adding their probabilities. This study was designed to replicate previous results and to test whether the violations of cumulative prospect theory might be eliminated or reduced by using formats for presentation of risky gambles in which cancellation and combination could be facilitated visually. Contrary to the idea that decision behavior contradicting cumulative prospect theory and the priority heuristic would be altered by use of these formats, however, data with two new graphical formats as well as fresh replication data continued to show the patterns of evidence that violate cumulative prospect theory, the priority heuristic, and the editing principles of combination and cancellation. Systematic violations of restricted branch independence also contradicted predictions of ``stripped'' prospect theory (subjectively weighted additive utility without the editing rules.

Probability and information theory, with applications to radar

CERN Document Server

Woodward, P M; Higinbotham, W

1964-01-01

Electronics and Instrumentation, Second Edition, Volume 3: Probability and Information Theory with Applications to Radar provides information pertinent to the development on research carried out in electronics and applied physics. This book presents the established mathematical techniques that provide the code in which so much of the mathematical theory of electronics and radar is expressed.Organized into eight chapters, this edition begins with an overview of the geometry of probability distributions in which moments play a significant role. This text then examines the mathematical methods in

Probability in physics

CERN Document Server

Hemmo, Meir

2012-01-01

What is the role and meaning of probability in physical theory, in particular in two of the most successful theories of our age, quantum physics and statistical mechanics? Laws once conceived as universal and deterministic, such as Newton‘s laws of motion, or the second law of thermodynamics, are replaced in these theories by inherently probabilistic laws. This collection of essays by some of the world‘s foremost experts presents an in-depth analysis of the meaning of probability in contemporary physics. Among the questions addressed are: How are probabilities defined? Are they objective or subjective? What is their  explanatory value? What are the differences between quantum and classical probabilities? The result is an informative and thought-provoking book for the scientifically inquisitive. 

Bayesian probability theory applications in the physical sciences

CERN Document Server

Linden, Wolfgang von der; Toussaint, Udo von

2014-01-01

From the basics to the forefront of modern research, this book presents all aspects of probability theory, statistics and data analysis from a Bayesian perspective for physicists and engineers. The book presents the roots, applications and numerical implementation of probability theory, and covers advanced topics such as maximum entropy distributions, stochastic processes, parameter estimation, model selection, hypothesis testing and experimental design. In addition, it explores state-of-the art numerical techniques required to solve demanding real-world problems. The book is ideal for students and researchers in physical sciences and engineering.

Risk Probabilities

DEFF Research Database (Denmark)

Rojas-Nandayapa, Leonardo

Tail probabilities of sums of heavy-tailed random variables are of a major importance in various branches of Applied Probability, such as Risk Theory, Queueing Theory, Financial Management, and are subject to intense research nowadays. To understand their relevance one just needs to think...... analytic expression for the distribution function of a sum of random variables. The presence of heavy-tailed random variables complicates the problem even more. The objective of this dissertation is to provide better approximations by means of sharp asymptotic expressions and Monte Carlo estimators...

Probability and logical structure of statistical theories

International Nuclear Information System (INIS)

Hall, M.J.W.

1988-01-01

A characterization of statistical theories is given which incorporates both classical and quantum mechanics. It is shown that each statistical theory induces an associated logic and joint probability structure, and simple conditions are given for the structure to be of a classical or quantum type. This provides an alternative for the quantum logic approach to axiomatic quantum mechanics. The Bell inequalities may be derived for those statistical theories that have a classical structure and satisfy a locality condition weaker than factorizability. The relation of these inequalities to the issue of hidden variable theories for quantum mechanics is discussed and clarified

Probability Theory, Not the Very Guide of Life

Science.gov (United States)

Juslin, Peter; Nilsson, Hakan; Winman, Anders

2009-01-01

Probability theory has long been taken as the self-evident norm against which to evaluate inductive reasoning, and classical demonstrations of violations of this norm include the conjunction error and base-rate neglect. Many of these phenomena require multiplicative probability integration, whereas people seem more inclined to linear additive…

Scoring Rules for Subjective Probability Distributions

DEFF Research Database (Denmark)

Harrison, Glenn W.; Martínez-Correa, Jimmy; Swarthout, J. Todd

2017-01-01

significantly due to risk aversion. We characterize an approach for eliciting the entire subjective belief distribution that is minimally biased due to risk aversion. We offer simulated examples to demonstrate the intuition of our approach. We also provide theory to formally characterize our framework. And we...... provide experimental evidence which corroborates our theoretical results. We conclude that for empirically plausible levels of risk aversion, one can reliably elicit most important features of the latent subjective belief distribution without undertaking calibration for risk attitudes providing one...

Problems in probability theory, mathematical statistics and theory of random functions

CERN Document Server

Sveshnikov, A A

1979-01-01

Problem solving is the main thrust of this excellent, well-organized workbook. Suitable for students at all levels in probability theory and statistics, the book presents over 1,000 problems and their solutions, illustrating fundamental theory and representative applications in the following fields: Random Events; Distribution Laws; Correlation Theory; Random Variables; Entropy & Information; Markov Processes; Systems of Random Variables; Limit Theorems; Data Processing; and more.The coverage of topics is both broad and deep, ranging from the most elementary combinatorial problems through lim

School and conference on probability theory

International Nuclear Information System (INIS)

Lawler, G.F.

2004-01-01

This volume includes expanded lecture notes from the School and Conference in Probability Theory held at ICTP in May, 2001. Probability theory is a very large area, too large for a single school and conference. The organizers, G. Lawler, C. Newman, and S. Varadhan chose to focus on a number of active research areas that have their roots in statistical physics. The pervasive theme in these lectures is trying to find the large time or large space behaviour of models defined on discrete lattices. Usually the definition of the model is relatively simple: either assigning a particular weight to each possible configuration (equilibrium statistical mechanics) or specifying the rules under which the system evolves (nonequilibrium statistical mechanics). Interacting particle systems is the area of probability that studies the evolution of particles (either finite or infinite in number) under random motions. The evolution of particles depends on the positions of the other particles; often one assumes that it depends only on the particles that are close to the particular particle. Thomas Liggett's lectures give an introduction to this very large area. Claudio Landim's follows up by discussing hydrodynamic limits of particle systems. The goal of this area is to describe the long time, large system size dynamics in terms of partial differential equations. The area of random media is concerned with the properties of materials or environments that are not homogeneous. Percolation theory studies one of the simplest stated models for impurities - taking a lattice and removing some of the vertices or bonds. Luiz Renato G. Fontes and Vladas Sidoravicius give a detailed introduction to this area. Random walk in random environment combines two sources of randomness - a particle performing stochastic motion in which the transition probabilities depend on position and have been chosen from some probability distribution. Alain-Sol Sznitman gives a survey of recent developments in this

Models for probability and statistical inference theory and applications

CERN Document Server

Stapleton, James H

2007-01-01

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...

Quantum interference of probabilities and hidden variable theories

International Nuclear Information System (INIS)

Srinivas, M.D.

1984-01-01

One of the fundamental contributions of Louis de Broglie, which does not get cited often, has been his analysis of the basic difference between the calculus of the probabilities as predicted by quantum theory and the usual calculus of probabilities - the one employed by most mathematicians, in its standard axiomatised version due to Kolmogorov. This paper is basically devoted to a discussion of the 'quantum interference of probabilities', discovered by de Broglie. In particular, it is shown that it is this feature of the quantum theoretic probabilities which leads to some serious constraints on the possible 'hidden-variable formulations' of quantum mechanics, including the celebrated theorem of Bell. (Auth.)

Concurrency meets probability: theory and practice (abstract)

NARCIS (Netherlands)

Katoen, Joost P.

Treating random phenomena in concurrency theory has a long tradition. Petri nets [18, 10] and process algebras [14] have been extended with probabilities. The same applies to behavioural semantics such as strong and weak (bi)simulation [1], and testing pre-orders [5]. Beautiful connections between

The Misapplication of Probability Theory in Quantum Mechanics

Science.gov (United States)

Racicot, Ronald

2014-03-01

This article is a revision of two papers submitted to the APS in the past two and a half years. In these papers, arguments and proofs are summarized for the following: (1) The wrong conclusion by EPR that Quantum Mechanics is incomplete, perhaps requiring the addition of ``hidden variables'' for completion. Theorems that assume such ``hidden variables,'' such as Bell's theorem, are also wrong. (2) Quantum entanglement is not a realizable physical phenomenon and is based entirely on assuming a probability superposition model for quantum spin. Such a model directly violates conservation of angular momentum. (3) Simultaneous multiple-paths followed by a quantum particle traveling through space also cannot possibly exist. Besides violating Noether's theorem, the multiple-paths theory is based solely on probability calculations. Probability calculations by themselves cannot possibly represent simultaneous physically real events. None of the reviews of the submitted papers actually refuted the arguments and evidence that was presented. These analyses should therefore be carefully evaluated since the conclusions reached have such important impact in quantum mechanics and quantum information theory.

Probability theory a comprehensive course

CERN Document Server

Klenke, Achim

2014-01-01

This second edition of the popular textbook contains a comprehensive course in modern probability theory. Overall, probabilistic concepts play an increasingly important role in mathematics, physics, biology, financial engineering and computer science. They help us in understanding magnetism, amorphous media, genetic diversity and the perils of random developments at financial markets, and they guide us in constructing more efficient algorithms.   To address these concepts, the title covers a wide variety of topics, many of which are not usually found in introductory textbooks, such as:   • limit theorems for sums of random variables • martingales • percolation • Markov chains and electrical networks • construction of stochastic processes • Poisson point process and infinite divisibility • large deviation principles and statistical physics • Brownian motion • stochastic integral and stochastic differential equations. The theory is developed rigorously and in a self-contained way, with the c...

Bayesian probability theory and inverse problems

International Nuclear Information System (INIS)

Kopec, S.

1994-01-01

Bayesian probability theory is applied to approximate solving of the inverse problems. In order to solve the moment problem with the noisy data, the entropic prior is used. The expressions for the solution and its error bounds are presented. When the noise level tends to zero, the Bayesian solution tends to the classic maximum entropy solution in the L 2 norm. The way of using spline prior is also shown. (author)

USING THE WEB-SERVICES WOLFRAM|ALPHA TO SOLVE PROBLEMS IN PROBABILITY THEORY

Directory of Open Access Journals (Sweden)

Taras Kobylnyk

2015-10-01

Full Text Available The trend towards the use of remote network resources on the Internet clearly delineated. Traditional training combined with increasingly networked, remote technologies become popular cloud computing. Research methods of probability theory are used in various fields. Of particular note is the use of methods of probability theory in psychological and educational research in statistical analysis of experimental data. Conducting such research is impossible without the use of modern information technology. Given the advantages of web-based software, the article describes web-service Wolfram|Alpha. Detailed analysis of the possibilities of using web-service Wolfram|Alpha for solving problems of probability theory. In the case studies described the results of queries for solving of probability theory, in particular the sections random events and random variables. Considered and analyzed the problem of the number of occurrences of event A in n independent trials using Wolfram|Alpha, detailed analysis of the possibilities of using the service Wolfram|Alpha for the study of continuous random variable that has a normal and uniform probability distribution, including calculating the probability of getting the value of a random variable in a given interval. The problem in applying the binomial and hypergeometric probability distribution of a discrete random variable and demonstrates the possibility of using the service Wolfram|Alpha for solving it.

Records via probability theory

CERN Document Server

Ahsanullah, Mohammad

2015-01-01

A lot of statisticians, actuarial mathematicians, reliability engineers, meteorologists, hydrologists, economists. Business and sport analysts deal with records which play important roles in various fields of statistics and its application. This book enables a reader to check his/her level of understanding of the theory of record values. We give basic formulae which are more important in the theory and present a lot of examples which illustrate the theoretical statements. For a beginner in record statistics, as well as for graduate students the study of our book needs the basic knowledge of the subject. A more advanced reader can use our book to polish his/her knowledge. An upgraded list of bibliography which will help a reader to enrich his/her theoretical knowledge and widen the experience of dealing with ordered observations, is also given in the book.

Probability

CERN Document Server

Shiryaev, A N

1996-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, ergodic theory, weak convergence of probability measures, stationary stochastic processes, and the Kalman-Bucy filter Many examples are discussed in detail, and there are a large number of exercises The book is accessible to advanced undergraduates and can be used as a text for self-study This new edition contains substantial revisions and updated references The reader will find a deeper study of topics such as the distance between probability measures, metrization of weak convergence, and contiguity of probability measures Proofs for a number of some important results which were merely stated in the first edition have been added The author included new material on the probability of large deviations, and on the central limit theorem for sums of dependent random variables

A Short History of Probability Theory and Its Applications

Science.gov (United States)

Debnath, Lokenath; Basu, Kanadpriya

2015-01-01

This paper deals with a brief history of probability theory and its applications to Jacob Bernoulli's famous law of large numbers and theory of errors in observations or measurements. Included are the major contributions of Jacob Bernoulli and Laplace. It is written to pay the tricentennial tribute to Jacob Bernoulli, since the year 2013…

Subjective Illness theory and coping

Directory of Open Access Journals (Sweden)

Gessmann H.-W.

2015-03-01

Full Text Available The article presents a view of a problem of subjective illness theory in context of coping behavior. The article compiles the results of the latest studies of coping; discloses the way subjective illness theory affects the illness coping and patient's health; presents the study of differences in coping behaviour of patients at risk of heart attack and oncology. The article is recommended for specialists, concerned with psychological reasons of pathogenic processes and coping strategies of patients.

Constructing diagnostic likelihood: clinical decisions using subjective versus statistical probability.

Science.gov (United States)

Kinnear, John; Jackson, Ruth

2017-07-01

Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability. This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information. For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, pprobability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Heuristics can produce surprisingly rational probability estimates: Comment on Costello and Watts (2014).

Science.gov (United States)

Nilsson, Håkan; Juslin, Peter; Winman, Anders

2016-01-01

Costello and Watts (2014) present a model assuming that people's knowledge of probabilities adheres to probability theory, but that their probability judgments are perturbed by a random noise in the retrieval from memory. Predictions for the relationships between probability judgments for constituent events and their disjunctions and conjunctions, as well as for sums of such judgments were derived from probability theory. Costello and Watts (2014) report behavioral data showing that subjective probability judgments accord with these predictions. Based on the finding that subjective probability judgments follow probability theory, Costello and Watts (2014) conclude that the results imply that people's probability judgments embody the rules of probability theory and thereby refute theories of heuristic processing. Here, we demonstrate the invalidity of this conclusion by showing that all of the tested predictions follow straightforwardly from an account assuming heuristic probability integration (Nilsson, Winman, Juslin, & Hansson, 2009). We end with a discussion of a number of previous findings that harmonize very poorly with the predictions by the model suggested by Costello and Watts (2014). (c) 2015 APA, all rights reserved).

Evaluation of probability and hazard in nuclear energy

International Nuclear Information System (INIS)

Novikov, V.Ya.; Romanov, N.L.

1979-01-01

Various methods of evaluation of accident probability on NPP are proposed because of NPP security statistic evaluation unreliability. The conception of subjective probability for quantitative analysis of security and hazard are described. Intrepretation of probability as real faith of an expert is assumed as a basis of the conception. It is suggested to study the event uncertainty in the framework of subjective probability theory which not only permits but demands to take into account expert opinions when evaluating the probability. These subjective expert evaluations effect to a certain extent the calculation of the usual mathematical event probability. The above technique is advantageous to use for consideration of a separate experiment or random event

Probabilities and Shannon's Entropy in the Everett Many-Worlds Theory

Directory of Open Access Journals (Sweden)

Andreas Wichert

2016-12-01

Full Text Available Following a controversial suggestion by David Deutsch that decision theory can solve the problem of probabilities in the Everett many-worlds we suggest that the probabilities are induced by Shannon's entropy that measures the uncertainty of events. We argue that a relational person prefers certainty to uncertainty due to fundamental biological principle of homeostasis.

[A probability wave theory on the ion movement across cell membrane].

Science.gov (United States)

Zhang, Hui; Xu, Jiadong; Niu, Zhongqi

2007-04-01

The ionic quantity across the channel of the cell membrane decides the cell in a certain life state. The theory analysis that existed on the bio-effects of the electro-magnetic field (EMF) does not unveil the relationship between the EMF exerted on the cell and the ionic quantity across the cell membrane. Based on the cell construction, the existed theory analysis and the experimental results, an ionic probability wave theory is proposed in this paper to explain the biological window-effects of the electromagnetic wave. The theory regards the membrane channel as the periodic potential barrier and gives the physical view of the ion movement across cell-membrane. The theory revises the relationship between ion's energy in cell channel and the frequency exerted EMF. After the application of the concept of the wave function, the ionic probability across the cell membrane is given by the method of the quantum mechanics. The numerical results analyze the physical factors that influences the ion's movement across the cell membrane. These results show that the theory can explain the phenomenon of the biological window-effects.

Reliability of structures by using probability and fatigue theories

International Nuclear Information System (INIS)

Lee, Ouk Sub; Kim, Dong Hyeok; Park, Yeon Chang

2008-01-01

Methodologies to calculate failure probability and to estimate the reliability of fatigue loaded structures are developed. The applicability of the methodologies is evaluated with the help of the fatigue crack growth models suggested by Paris and Walker. The probability theories such as the FORM (first order reliability method), the SORM (second order reliability method) and the MCS (Monte Carlo simulation) are utilized. It is found that the failure probability decreases with the increase of the design fatigue life and the applied minimum stress, the decrease of the initial edge crack size, the applied maximum stress and the slope of Paris equation. Furthermore, according to the sensitivity analysis of random variables, the slope of Pairs equation affects the failure probability dominantly among other random variables in the Paris and the Walker models

A short course on measure and probability theories

Energy Technology Data Exchange (ETDEWEB)

Pebay, Philippe Pierre

2004-02-01

This brief Introduction to Measure Theory, and its applications to Probabilities, corresponds to the lecture notes of a seminar series given at Sandia National Laboratories in Livermore, during the spring of 2003. The goal of these seminars was to provide a minimal background to Computational Combustion scientists interested in using more advanced stochastic concepts and methods, e.g., in the context of uncertainty quantification. Indeed, most mechanical engineering curricula do not provide students with formal training in the field of probability, and even in less in measure theory. However, stochastic methods have been used more and more extensively in the past decade, and have provided more successful computational tools. Scientists at the Combustion Research Facility of Sandia National Laboratories have been using computational stochastic methods for years. Addressing more and more complex applications, and facing difficult problems that arose in applications showed the need for a better understanding of theoretical foundations. This is why the seminar series was launched, and these notes summarize most of the concepts which have been discussed. The goal of the seminars was to bring a group of mechanical engineers and computational combustion scientists to a full understanding of N. WIENER'S polynomial chaos theory. Therefore, these lectures notes are built along those lines, and are not intended to be exhaustive. In particular, the author welcomes any comments or criticisms.

Comparison between the Health Belief Model and Subjective Expected Utility Theory: predicting incontinence prevention behaviour in post-partum women.

Science.gov (United States)

Dolman, M; Chase, J

1996-08-01

A small-scale study was undertaken to test the relative predictive power of the Health Belief Model and Subjective Expected Utility Theory for the uptake of a behaviour (pelvic floor exercises) to reduce post-partum urinary incontinence in primigravida females. A structured questionnaire was used to gather data relevant to both models from a sample antenatal and postnatal primigravida women. Questions examined the perceived probability of becoming incontinent, the perceived (dis)utility of incontinence, the perceived probability of pelvic floor exercises preventing future urinary incontinence, the costs and benefits of performing pelvic floor exercises and sources of information and knowledge about incontinence. Multiple regression analysis focused on whether or not respondents intended to perform pelvic floor exercises and the factors influencing their decisions. Aggregated data were analysed to compare the Health Belief Model and Subjective Expected Utility Theory directly.

Joint probabilities of noncommuting observables and the Einstein-Podolsky-Rosen question in Wiener-Siegel quantum theory

International Nuclear Information System (INIS)

Warnock, R.L.

1996-02-01

Ordinary quantum theory is a statistical theory without an underlying probability space. The Wiener-Siegel theory provides a probability space, defined in terms of the usual wave function and its ''stochastic coordinates''; i.e., projections of its components onto differentials of complex Wiener processes. The usual probabilities of quantum theory emerge as measures of subspaces defined by inequalities on stochastic coordinates. Since each point α of the probability space is assigned values (or arbitrarily small intervals) of all observables, the theory gives a pseudo-classical or ''hidden-variable'' view in which normally forbidden concepts are allowed. Joint probabilities for values of noncommuting variables are well-defined. This paper gives a brief description of the theory, including a new generalization to incorporate spin, and reports the first concrete calculation of a joint probability for noncommuting components of spin of a single particle. Bohm's form of the Einstein-Podolsky-Rosen Gedankenexperiment is discussed along the lines of Carlen's paper at this Congress. It would seem that the ''EPR Paradox'' is avoided, since to each α the theory assigns opposite values for spin components of two particles in a singlet state, along any axis. In accordance with Bell's ideas, the price to pay for this attempt at greater theoretical detail is a disagreement with usual quantum predictions. The disagreement is computed and found to be large

Probability-1

CERN Document Server

Shiryaev, Albert N

2016-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, the measure-theoretic foundations of probability theory, weak convergence of probability measures, and the central limit theorem. Many examples are discussed in detail, and there are a large number of exercises. The book is accessible to advanced undergraduates and can be used as a text for independent study. To accommodate the greatly expanded material in the third edition of Probability, the book is now divided into two volumes. This first volume contains updated references and substantial revisions of the first three chapters of the second edition. In particular, new material has been added on generating functions, the inclusion-exclusion principle, theorems on monotonic classes (relying on a detailed treatment of “π-λ” systems), and the fundamental theorems of mathematical statistics.

Probability, random variables, and random processes theory and signal processing applications

CERN Document Server

Shynk, John J

2012-01-01

Probability, Random Variables, and Random Processes is a comprehensive textbook on probability theory for engineers that provides a more rigorous mathematical framework than is usually encountered in undergraduate courses. It is intended for first-year graduate students who have some familiarity with probability and random variables, though not necessarily of random processes and systems that operate on random signals. It is also appropriate for advanced undergraduate students who have a strong mathematical background. The book has the following features: Several app

Main factors for fatigue failure probability of pipes subjected to fluid thermal fluctuation

International Nuclear Information System (INIS)

Machida, Hideo; Suzuki, Masaaki; Kasahara, Naoto

2015-01-01

It is very important to grasp failure probability and failure mode appropriately to carry out risk reduction measures of nuclear power plants. To clarify the important factors for failure probability and failure mode of pipes subjected to fluid thermal fluctuation, failure probability analyses were performed by changing the values of a stress range, stress ratio, stress components and threshold of stress intensity factor range. The important factors for the failure probability are range, stress ratio (mean stress condition) and threshold of stress intensity factor range. The important factor for the failure mode is a circumferential angle range of fluid thermal fluctuation. When a large fluid thermal fluctuation acts on the entire circumferential surface of the pipe, the probability of pipe breakage increases, calling for measures to prevent such a failure and reduce the risk to the plant. When the circumferential angle subjected to fluid thermal fluctuation is small, the failure mode of piping is leakage and the corrective maintenance might be applicable from the viewpoint of risk to the plant. (author)

Exaggerated risk: prospect theory and probability weighting in risky choice.

Science.gov (United States)

Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick

2009-11-01

In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and Kahneman's (1992) prospect theory, we found that the weighting function required to model precautionary decisions differed from that required for monetary gambles. This result indicates a failure of the descriptive invariance axiom of expected utility theory. For precautionary decisions, people overweighted small, medium-sized, and moderately large probabilities-they exaggerated risks. This effect is not anticipated by prospect theory or experience-based decision research (Hertwig, Barron, Weber, & Erev, 2004). We found evidence that exaggerated risk is caused by the accessibility of events in memory: The weighting function varies as a function of the accessibility of events. This suggests that people's experiences of events leak into decisions even when risk information is explicitly provided. Our findings highlight a need to investigate how variation in decision content produces variation in preferences for risk.

The Subject, Feminist Theory and Latin American Texts

Directory of Open Access Journals (Sweden)

Sara Castro-Klaren

1996-01-01

Full Text Available From a feminist perspective, this essay reviews and analyzes the interaction between metropolitan feminist theories and their interphase with the academic criticism of texts written by Latin American women. Discussion focuses on the question of the subject, which the author believes to be paramount in feminist theory, in as much as the construction of gender and the historical subordination of women devolve on the play of difference and identity. This paper examines how the problematic assumption by feminist theorists in the North American academy of Freudian and Lacanian theories of the subject pose unresolved problems and unanticipated complications to subsequent deployment of this subject theory as modes of interpretation of texts written by women in Latin America or even to the emancipatory goals on feminists in the academy. This is a case where "traveling theory" must be examined and evaluated very carefully. The second part of the paper concentrates on the feminist challenges that have been already made to both Freudian and Lacanian theories of the feminine. It highlights the work of Jane Flax, Nacy Chodorov, Gayatri Spivak and Judith Butler in suggesting a way out of theories that rely on the primacy of the male subject formation and therefore occlude and preclude the investigation of the modes of women's agency.

The force distribution probability function for simple fluids by density functional theory.

Science.gov (United States)

Rickayzen, G; Heyes, D M

2013-02-28

Classical density functional theory (DFT) is used to derive a formula for the probability density distribution function, P(F), and probability distribution function, W(F), for simple fluids, where F is the net force on a particle. The final formula for P(F) ∝ exp(-AF(2)), where A depends on the fluid density, the temperature, and the Fourier transform of the pair potential. The form of the DFT theory used is only applicable to bounded potential fluids. When combined with the hypernetted chain closure of the Ornstein-Zernike equation, the DFT theory for W(F) agrees with molecular dynamics computer simulations for the Gaussian and bounded soft sphere at high density. The Gaussian form for P(F) is still accurate at lower densities (but not too low density) for the two potentials, but with a smaller value for the constant, A, than that predicted by the DFT theory.

Unification of field theory and maximum entropy methods for learning probability densities

Science.gov (United States)

Kinney, Justin B.

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

Unification of field theory and maximum entropy methods for learning probability densities.

Science.gov (United States)

Kinney, Justin B

2015-09-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

Relationship between Future Time Orientation and Item Nonresponse on Subjective Probability Questions: A Cross-Cultural Analysis.

Science.gov (United States)

Lee, Sunghee; Liu, Mingnan; Hu, Mengyao

2017-06-01

Time orientation is an unconscious yet fundamental cognitive process that provides a framework for organizing personal experiences in temporal categories of past, present and future, reflecting the relative emphasis given to these categories. Culture lies central to individuals' time orientation, leading to cultural variations in time orientation. For example, people from future-oriented cultures tend to emphasize the future and store information relevant for the future more than those from present- or past-oriented cultures. For survey questions that ask respondents to report expected probabilities of future events, this may translate into culture-specific question difficulties, manifested through systematically varying "I don't know" item nonresponse rates. This study drew on the time orientation theory and examined culture-specific nonresponse patterns on subjective probability questions using methodologically comparable population-based surveys from multiple countries. The results supported our hypothesis. Item nonresponse rates on these questions varied significantly in the way that future-orientation at the group as well as individual level was associated with lower nonresponse rates. This pattern did not apply to non-probability questions. Our study also suggested potential nonresponse bias. Examining culture-specific constructs, such as time orientation, as a framework for measurement mechanisms may contribute to improving cross-cultural research.

On Dobrushin's way from probability theory to statistical physics

CERN Document Server

Minlos, R A; Suhov, Yu M; Suhov, Yu

2000-01-01

R. Dobrushin worked in several branches of mathematics (probability theory, information theory), but his deepest influence was on mathematical physics. He was one of the founders of the rigorous study of statistical physics. When Dobrushin began working in that direction in the early sixties, only a few people worldwide were thinking along the same lines. Now there is an army of researchers in the field. This collection is devoted to the memory of R. L. Dobrushin. The authors who contributed to this collection knew him quite well and were his colleagues. The title, "On Dobrushin's Way", is mea

Measuring inequity aversion in a heterogeneous population using experimental decisions and subjective probabilities

NARCIS (Netherlands)

Bellemare, C.; Kroger, S.; van Soest, A.H.O.

2008-01-01

We combine choice data in the ultimatum game with the expectations of proposers elicited by subjective probability questions to estimate a structural model of decision making under uncertainty. The model, estimated using a large representative sample of subjects from the Dutch population, allows

Perturbation theory and collision probability formalism. Vol. 2

Energy Technology Data Exchange (ETDEWEB)

Nasr, M [National Center for Nuclear Safety and Radiation Control, Atomic Energy Authority, Cairo (Egypt)

1996-03-01

Perturbation theory is commonly used in evaluating the activity effects, particularly those resulting from small and localized perturbation in multiplying media., e.g. in small sample reactivity measurements. The Boltzmann integral transport equation is generally used for evaluating the direct and adjoint fluxes in the heterogenous lattice cells to be used in the perturbation equations. When applying perturbation theory in this formalism, a term involving the perturbation effects on the special transfer kernel arises. This term is difficult to evaluate correctly, since it involves an integration all over the entire system. The main advantage of the perturbation theory which is the limitation of the integration procedure on the perturbation region is found to be of no practical use in such cases. In the present work, the perturbation equation in the collision probability formalism is analyzed. A mathematical treatment of the term in question is performed. A new mathematical expression for this term is derived. The new expression which can be estimated easily is derived.

Dopaminergic Drug Effects on Probability Weighting during Risky Decision Making.

Science.gov (United States)

Ojala, Karita E; Janssen, Lieneke K; Hashemi, Mahur M; Timmer, Monique H M; Geurts, Dirk E M; Ter Huurne, Niels P; Cools, Roshan; Sescousse, Guillaume

2018-01-01

Dopamine has been associated with risky decision-making, as well as with pathological gambling, a behavioral addiction characterized by excessive risk-taking behavior. However, the specific mechanisms through which dopamine might act to foster risk-taking and pathological gambling remain elusive. Here we test the hypothesis that this might be achieved, in part, via modulation of subjective probability weighting during decision making. Human healthy controls ( n = 21) and pathological gamblers ( n = 16) played a decision-making task involving choices between sure monetary options and risky gambles both in the gain and loss domains. Each participant played the task twice, either under placebo or the dopamine D 2 /D 3 receptor antagonist sulpiride, in a double-blind counterbalanced design. A prospect theory modelling approach was used to estimate subjective probability weighting and sensitivity to monetary outcomes. Consistent with prospect theory, we found that participants presented a distortion in the subjective weighting of probabilities, i.e., they overweighted low probabilities and underweighted moderate to high probabilities, both in the gain and loss domains. Compared with placebo, sulpiride attenuated this distortion in the gain domain. Across drugs, the groups did not differ in their probability weighting, although gamblers consistently underweighted losing probabilities in the placebo condition. Overall, our results reveal that dopamine D 2 /D 3 receptor antagonism modulates the subjective weighting of probabilities in the gain domain, in the direction of more objective, economically rational decision making.

Dopaminergic Drug Effects on Probability Weighting during Risky Decision Making

Science.gov (United States)

Timmer, Monique H. M.; ter Huurne, Niels P.

2018-01-01

Abstract Dopamine has been associated with risky decision-making, as well as with pathological gambling, a behavioral addiction characterized by excessive risk-taking behavior. However, the specific mechanisms through which dopamine might act to foster risk-taking and pathological gambling remain elusive. Here we test the hypothesis that this might be achieved, in part, via modulation of subjective probability weighting during decision making. Human healthy controls (n = 21) and pathological gamblers (n = 16) played a decision-making task involving choices between sure monetary options and risky gambles both in the gain and loss domains. Each participant played the task twice, either under placebo or the dopamine D2/D3 receptor antagonist sulpiride, in a double-blind counterbalanced design. A prospect theory modelling approach was used to estimate subjective probability weighting and sensitivity to monetary outcomes. Consistent with prospect theory, we found that participants presented a distortion in the subjective weighting of probabilities, i.e., they overweighted low probabilities and underweighted moderate to high probabilities, both in the gain and loss domains. Compared with placebo, sulpiride attenuated this distortion in the gain domain. Across drugs, the groups did not differ in their probability weighting, although gamblers consistently underweighted losing probabilities in the placebo condition. Overall, our results reveal that dopamine D2/D3 receptor antagonism modulates the subjective weighting of probabilities in the gain domain, in the direction of more objective, economically rational decision making. PMID:29632870

On the subjectivity of personality theory.

Science.gov (United States)

Atwood, G E; Tomkins, S S

1976-04-01

Every theorist of personality views the human condition from the unique perspective of his own individuality. As a consequence, personality theories are strongly influenced by personal and subjective factors. These influences are partially responsible for the present day lack of consensus in psychology as to basic conceptual frameworks for the study of man. The science of human personality can achieve a greater degree of consensus and generality only if it begins to turn back on itself and question its own psychological foundations. The role of subjective and personal factors in this field can be studied and made more explicit by means of a psychobiographical method which interprets the major ideas of personality theories in the light of the formative experiences in the respective theorists' lives. This method is briefly illustrated by an examination of the influence of personal experiences on theoretical concepts in the work of Carl Jung, Carl Rogers, Wilhelm Reich, and Gordon Allport. The subjective factors disclosed by psychobiographical analysis can bee seen to interact with influences stemming from the intellectual and historical context within which the theorist work. The psychobiographical study of personality theory is only one part of a larger discipline, the psychology of knowledge, which would study the role of subjective and personal factors in the structure of man's knowledge in general.

Communicating through Probabilities: Does Quantum Theory Optimize the Transfer of Information?

Directory of Open Access Journals (Sweden)

William K. Wootters

2013-08-01

Full Text Available A quantum measurement can be regarded as a communication channel, in which the parameters of the state are expressed only in the probabilities of the outcomes of the measurement. We begin this paper by considering, in a non-quantum-mechanical setting, the problem of communicating through probabilities. For example, a sender, Alice, wants to convey to a receiver, Bob, the value of a continuous variable, θ, but her only means of conveying this value is by sending Bob a coin in which the value of θ is encoded in the probability of heads. We ask what the optimal encoding is when Bob will be allowed to flip the coin only a finite number of times. As the number of tosses goes to infinity, we find that the optimal encoding is the same as what nature would do if we lived in a world governed by real-vector-space quantum theory. We then ask whether the problem might be modified, so that the optimal communication strategy would be consistent with standard, complex-vector-space quantum theory.

Higher risk of probable mental emotional disorder in low or severe vision subjects

Directory of Open Access Journals (Sweden)

Lutfah Rif’ati

2012-07-01

health problem priority in Indonesia. This paper presents an assessment of severe visual impairments related to the risk of MED. Methods: This paper assessed a part of Basic Health Research (Riskesdas 2007 data. For this assessment, subjects 15 years old or more had their visual acuity measured using the Snellen chart and their mental health status determined using the Self Reporting Questionnaire (SRQ 20. A subject was considered to have probable MED if the subject had a total score of 6 or more on the SRQ. Based on the measure of visual acuity, visual acuity was divided into 3 categories: normal/mild (20/20 to 20/60; low vision (less than 20/60 to 3/60; and blind (less than 3/60 to 0/0. Results: Among 972,989 subjects, 554,886 were aged 15 years or older. 11.4% of the subjects had probable MED. The prevalence of low vision and blindness was 5.1% and 0.9%, respectively. Compared to subjects with normal or mild visual impairments, subjects with low vision had a 74% increased risk for probable MED [adjusted relative risk (RRa=1,75; 95% confidence interval (CI=1,71-1,79].  Blind subjects had a 2.7-fold risk to be probable MED (RRa=2.69; 95% CI=2.60-2.78] compared to subjects with normal or mild visual impairments. Conclusion: Visual impairment severity increased probable MED risk. Therefore, visual impairment subjects need more attention on probable MED. (Health Science Indones 2011;2:9-13

The first cycle of the reflective pedagogical paradigm implementation in the introduction probability theory course

Science.gov (United States)

Julie, Hongki

2017-08-01

One of purposes of this study was describing the steps of the teaching and learning process if the teacher in the Introduction Probability Theory course wanted to teach about the event probability by using the reflective pedagogical paradigm (RPP) and describing the results achieved by the students. The study consisted of three cycles, but the results would be presented in this paper was limited to the results obtained in the first cycle. Stages conducted by the researcher in the first cycle could be divided into five stages, namely (1) to know the students' context, (2) to plan and provide student learning experiences, (3) to facilitate students in actions, (4) to ask students to make a reflection and (5) to evaluate. The type of research used in this research was descriptive qualitative and quantitative research. The students' learning experience, the students' action, and the students' reflection would be described qualitatively. The student evaluation results would be described quantitatively. The research subject in this study was 38 students taking the introduction probability theory course in class C. From the students' reflection, still quite a lot of students were not complete in writing concepts that they have learned and / or have not been precise in describing the relationships between concepts that they have learned. From the students' evaluation, 85.29% students got score under 7. If examined more deeply, the most difficulty of students were in the mathematical horizontal process. As a result, they had difficulty in performing the mathematical vertical process.

Estimation and asymptotic theory for transition probabilities in Markov Renewal Multi–state models

NARCIS (Netherlands)

Spitoni, C.; Verduijn, M.; Putter, H.

2012-01-01

In this paper we discuss estimation of transition probabilities for semi–Markov multi–state models. Non–parametric and semi–parametric estimators of the transition probabilities for a large class of models (forward going models) are proposed. Large sample theory is derived using the functional

A subjective utilitarian theory of moral judgment.

Science.gov (United States)

Cohen, Dale J; Ahn, Minwoo

2016-10-01

Current theories hypothesize that moral judgments are difficult because rational and emotional decision processes compete. We present a fundamentally different theory of moral judgment: the Subjective Utilitarian Theory of moral judgment. The Subjective Utilitarian Theory posits that people try to identify and save the competing item with the greatest "personal value." Moral judgments become difficult only when the competing items have similar personal values. In Experiment 1, we estimate the personal values of 104 items. In Experiments 2-5, we show that the distributional overlaps of the estimated personal values account for over 90% of the variance in reaction times (RTs) and response choices in a moral judgment task. Our model fundamentally restructures our understanding of moral judgments from a competition between decision processes to a competition between similarly valued items. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The maximum entropy method of moments and Bayesian probability theory

Science.gov (United States)

Bretthorst, G. Larry

2013-08-01

The problem of density estimation occurs in many disciplines. For example, in MRI it is often necessary to classify the types of tissues in an image. To perform this classification one must first identify the characteristics of the tissues to be classified. These characteristics might be the intensity of a T1 weighted image and in MRI many other types of characteristic weightings (classifiers) may be generated. In a given tissue type there is no single intensity that characterizes the tissue, rather there is a distribution of intensities. Often this distributions can be characterized by a Gaussian, but just as often it is much more complicated. Either way, estimating the distribution of intensities is an inference problem. In the case of a Gaussian distribution, one must estimate the mean and standard deviation. However, in the Non-Gaussian case the shape of the density function itself must be inferred. Three common techniques for estimating density functions are binned histograms [1, 2], kernel density estimation [3, 4], and the maximum entropy method of moments [5, 6]. In the introduction, the maximum entropy method of moments will be reviewed. Some of its problems and conditions under which it fails will be discussed. Then in later sections, the functional form of the maximum entropy method of moments probability distribution will be incorporated into Bayesian probability theory. It will be shown that Bayesian probability theory solves all of the problems with the maximum entropy method of moments. One gets posterior probabilities for the Lagrange multipliers, and, finally, one can put error bars on the resulting estimated density function.

Self-Organized Complexity and Coherent Infomax from the Viewpoint of Jaynes’s Probability Theory

Directory of Open Access Journals (Sweden)

William A. Phillips

2012-01-01

Full Text Available This paper discusses concepts of self-organized complexity and the theory of Coherent Infomax in the light of Jaynes’s probability theory. Coherent Infomax, shows, in principle, how adaptively self-organized complexity can be preserved and improved by using probabilistic inference that is context-sensitive. It argues that neural systems do this by combining local reliability with flexible, holistic, context-sensitivity. Jaynes argued that the logic of probabilistic inference shows it to be based upon Bayesian and Maximum Entropy methods or special cases of them. He presented his probability theory as the logic of science; here it is considered as the logic of life. It is concluded that the theory of Coherent Infomax specifies a general objective for probabilistic inference, and that contextual interactions in neural systems perform functions required of the scientist within Jaynes’s theory.

Non-Archimedean Probability

NARCIS (Netherlands)

Benci, Vieri; Horsten, Leon; Wenmackers, Sylvia

We propose an alternative approach to probability theory closely related to the framework of numerosity theory: non-Archimedean probability (NAP). In our approach, unlike in classical probability theory, all subsets of an infinite sample space are measurable and only the empty set gets assigned

Fusing probability density function into Dempster-Shafer theory of evidence for the evaluation of water treatment plant.

Science.gov (United States)

Chowdhury, Shakhawat

2013-05-01

The evaluation of the status of a municipal drinking water treatment plant (WTP) is important. The evaluation depends on several factors, including, human health risks from disinfection by-products (R), disinfection performance (D), and cost (C) of water production and distribution. The Dempster-Shafer theory (DST) of evidence can combine the individual status with respect to R, D, and C to generate a new indicator, from which the overall status of a WTP can be evaluated. In the DST, the ranges of different factors affecting the overall status are divided into several segments. The basic probability assignments (BPA) for each segment of these factors are provided by multiple experts, which are then combined to obtain the overall status. In assigning the BPA, the experts use their individual judgments, which can impart subjective biases in the overall evaluation. In this research, an approach has been introduced to avoid the assignment of subjective BPA. The factors contributing to the overall status were characterized using the probability density functions (PDF). The cumulative probabilities for different segments of these factors were determined from the cumulative density function, which were then assigned as the BPA for these factors. A case study is presented to demonstrate the application of PDF in DST to evaluate a WTP, leading to the selection of the required level of upgradation for the WTP.

Ergodic theory, interpretations of probability and the foundations of statistical mechanics

NARCIS (Netherlands)

van Lith, J.H.

2001-01-01

The traditional use of ergodic theory in the foundations of equilibrium statistical mechanics is that it provides a link between thermodynamic observables and microcanonical probabilities. First of all, the ergodic theorem demonstrates the equality of microcanonical phase averages and infinite time

Constructor theory of probability

Science.gov (United States)

2016-01-01

Unitary quantum theory, having no Born Rule, is non-probabilistic. Hence the notorious problem of reconciling it with the unpredictability and appearance of stochasticity in quantum measurements. Generalizing and improving upon the so-called ‘decision-theoretic approach’, I shall recast that problem in the recently proposed constructor theory of information—where quantum theory is represented as one of a class of superinformation theories, which are local, non-probabilistic theories conforming to certain constructor-theoretic conditions. I prove that the unpredictability of measurement outcomes (to which constructor theory gives an exact meaning) necessarily arises in superinformation theories. Then I explain how the appearance of stochasticity in (finitely many) repeated measurements can arise under superinformation theories. And I establish sufficient conditions for a superinformation theory to inform decisions (made under it) as if it were probabilistic, via a Deutsch–Wallace-type argument—thus defining a class of decision-supporting superinformation theories. This broadens the domain of applicability of that argument to cover constructor-theory compliant theories. In addition, in this version some of the argument's assumptions, previously construed as merely decision-theoretic, follow from physical properties expressed by constructor-theoretic principles. PMID:27616914

Probability an introduction

CERN Document Server

Goldberg, Samuel

1960-01-01

Excellent basic text covers set theory, probability theory for finite sample spaces, binomial theorem, probability distributions, means, standard deviations, probability function of binomial distribution, more. Includes 360 problems with answers for half.

Probability theory versus simulation of petroleum potential in play analysis

Science.gov (United States)

Crovelli, R.A.

1987-01-01

An analytic probabilistic methodology for resource appraisal of undiscovered oil and gas resources in play analysis is presented. This play-analysis methodology is a geostochastic system for petroleum resource appraisal in explored as well as frontier areas. An objective was to replace an existing Monte Carlo simulation method in order to increase the efficiency of the appraisal process. Underlying the two methods is a single geologic model which considers both the uncertainty of the presence of the assessed hydrocarbon and its amount if present. The results of the model are resource estimates of crude oil, nonassociated gas, dissolved gas, and gas for a geologic play in terms of probability distributions. The analytic method is based upon conditional probability theory and a closed form solution of all means and standard deviations, along with the probabilities of occurrence. ?? 1987 J.C. Baltzer A.G., Scientific Publishing Company.

Aspects of a representation of quantum theory in terms of classical probability theory by means of integration in Hilbert space

International Nuclear Information System (INIS)

Bach, A.

1981-01-01

A representation of quantum mechanics in terms of classical probability theory by means of integration in Hilbert space is discussed. This formal hidden-variables representation is analysed in the context of impossibility proofs concerning hidden-variables theories. The structural analogy of this formulation of quantum theory with classical statistical mechanics is used to elucidate the difference between classical mechanics and quantum mechanics. (author)

Opera house acoustics based on subjective preference theory

CERN Document Server

Ando, Yoichi

2015-01-01

This book focuses on opera house acoustics based on subjective preference theory; it targets researchers in acoustics and vision who are working in physics, psychology, and brain physiology. This book helps readers to understand any subjective attributes in relation to objective parameters based on the powerful and workable model of the auditory system. It is reconfirmed here that the well-known Helmholtz theory, which was based on a peripheral model of the auditory system, may not well describe pitch, timbre, and duration as well as the spatial sensations described in this book, nor overall responses such as subjective preference of sound fields and the annoyance of environmental noise.

Unification of field theory and maximum entropy methods for learning probability densities

OpenAIRE

Kinney, Justin B.

2014-01-01

The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy de...

Bayesian Probability Theory

Science.gov (United States)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

The relevance of the early history of probability theory to current risk assessment practices in mental health care.

Science.gov (United States)

Large, Matthew

2013-12-01

Probability theory is at the base of modern concepts of risk assessment in mental health. The aim of the current paper is to review the key developments in the early history of probability theory in order to enrich our understanding of current risk assessment practices.

Reality, Causality, and Probability, from Quantum Mechanics to Quantum Field Theory

Science.gov (United States)

Plotnitsky, Arkady

2015-10-01

These three lectures consider the questions of reality, causality, and probability in quantum theory, from quantum mechanics to quantum field theory. They do so in part by exploring the ideas of the key founding figures of the theory, such N. Bohr, W. Heisenberg, E. Schrödinger, or P. A. M. Dirac. However, while my discussion of these figures aims to be faithful to their thinking and writings, and while these lectures are motivated by my belief in the helpfulness of their thinking for understanding and advancing quantum theory, this project is not driven by loyalty to their ideas. In part for that reason, these lectures also present different and even conflicting ways of thinking in quantum theory, such as that of Bohr or Heisenberg vs. that of Schrödinger. The lectures, most especially the third one, also consider new physical, mathematical, and philosophical complexities brought in by quantum field theory vis-à-vis quantum mechanics. I close by briefly addressing some of the implications of the argument presented here for the current state of fundamental physics.

Real analysis and probability

CERN Document Server

Ash, Robert B; Lukacs, E

1972-01-01

Real Analysis and Probability provides the background in real analysis needed for the study of probability. Topics covered range from measure and integration theory to functional analysis and basic concepts of probability. The interplay between measure theory and topology is also discussed, along with conditional probability and expectation, the central limit theorem, and strong laws of large numbers with respect to martingale theory.Comprised of eight chapters, this volume begins with an overview of the basic concepts of the theory of measure and integration, followed by a presentation of var

The pleasures of probability

CERN Document Server

Isaac, Richard

1995-01-01

The ideas of probability are all around us. Lotteries, casino gambling, the al­ most non-stop polling which seems to mold public policy more and more­ these are a few of the areas where principles of probability impinge in a direct way on the lives and fortunes of the general public. At a more re­ moved level there is modern science which uses probability and its offshoots like statistics and the theory of random processes to build mathematical descriptions of the real world. In fact, twentieth-century physics, in embrac­ ing quantum mechanics, has a world view that is at its core probabilistic in nature, contrary to the deterministic one of classical physics. In addition to all this muscular evidence of the importance of probability ideas it should also be said that probability can be lots of fun. It is a subject where you can start thinking about amusing, interesting, and often difficult problems with very little mathematical background. In this book, I wanted to introduce a reader with at least a fairl...

An introduction to decision theory

NARCIS (Netherlands)

Peterson, M.B.

2009-01-01

This up-to-date introduction to decision theory offers comprehensive and accessible discussions of decision making under ignorance and risk, the foundations of utility theory, the debate over subjective and objective probability, Bayesianism, causal decision theory, game theory and social choice

Ruin probabilities

DEFF Research Database (Denmark)

Asmussen, Søren; Albrecher, Hansjörg

The book gives a comprehensive treatment of the classical and modern ruin probability theory. Some of the topics are Lundberg's inequality, the Cramér-Lundberg approximation, exact solutions, other approximations (e.g., for heavy-tailed claim size distributions), finite horizon ruin probabilities......, extensions of the classical compound Poisson model to allow for reserve-dependent premiums, Markov-modulation, periodicity, change of measure techniques, phase-type distributions as a computational vehicle and the connection to other applied probability areas, like queueing theory. In this substantially...... updated and extended second version, new topics include stochastic control, fluctuation theory for Levy processes, Gerber–Shiu functions and dependence....

Quantum Probabilities as Behavioral Probabilities

Directory of Open Access Journals (Sweden)

Vyacheslav I. Yukalov

2017-03-01

Full Text Available We demonstrate that behavioral probabilities of human decision makers share many common features with quantum probabilities. This does not imply that humans are some quantum objects, but just shows that the mathematics of quantum theory is applicable to the description of human decision making. The applicability of quantum rules for describing decision making is connected with the nontrivial process of making decisions in the case of composite prospects under uncertainty. Such a process involves deliberations of a decision maker when making a choice. In addition to the evaluation of the utilities of considered prospects, real decision makers also appreciate their respective attractiveness. Therefore, human choice is not based solely on the utility of prospects, but includes the necessity of resolving the utility-attraction duality. In order to justify that human consciousness really functions similarly to the rules of quantum theory, we develop an approach defining human behavioral probabilities as the probabilities determined by quantum rules. We show that quantum behavioral probabilities of humans do not merely explain qualitatively how human decisions are made, but they predict quantitative values of the behavioral probabilities. Analyzing a large set of empirical data, we find good quantitative agreement between theoretical predictions and observed experimental data.

Interpretations of probability

CERN Document Server

Khrennikov, Andrei

2009-01-01

This is the first fundamental book devoted to non-Kolmogorov probability models. It provides a mathematical theory of negative probabilities, with numerous applications to quantum physics, information theory, complexity, biology and psychology. The book also presents an interesting model of cognitive information reality with flows of information probabilities, describing the process of thinking, social, and psychological phenomena.

Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

International Nuclear Information System (INIS)

Vourdas, A.

2014-01-01

The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H 1 ,H 2 ), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H 1 ),P(H 2 ), to the subspaces H 1 , H 2 . As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities

Foundations of probability

International Nuclear Information System (INIS)

Fraassen, B.C. van

1979-01-01

The interpretation of probabilities in physical theories are considered, whether quantum or classical. The following points are discussed 1) the functions P(μ, Q) in terms of which states and propositions can be represented, are classical (Kolmogoroff) probabilities, formally speaking, 2) these probabilities are generally interpreted as themselves conditional, and the conditions are mutually incompatible where the observables are maximal and 3) testing of the theory typically takes the form of confronting the expectation values of observable Q calculated with probability measures P(μ, Q) for states μ; hence, of comparing the probabilities P(μ, Q)(E) with the frequencies of occurrence of the corresponding events. It seems that even the interpretation of quantum mechanics, in so far as it concerns what the theory says about the empirical (i.e. actual, observable) phenomena, deals with the confrontation of classical probability measures with observable frequencies. This confrontation is studied. (Auth./C.F.)

Geometric function theory: a modern view of a classical subject

International Nuclear Information System (INIS)

Crowdy, Darren

2008-01-01

Geometric function theory is a classical subject. Yet it continues to find new applications in an ever-growing variety of areas such as modern mathematical physics, more traditional fields of physics such as fluid dynamics, nonlinear integrable systems theory and the theory of partial differential equations. This paper surveys, with a view to modern applications, open problems and challenges in this subject. Here we advocate an approach based on the use of the Schottky–Klein prime function within a Schottky model of compact Riemann surfaces. (open problem)

Conditional Probabilities in the Excursion Set Theory. Generic Barriers and non-Gaussian Initial Conditions

CERN Document Server

De Simone, Andrea; Riotto, Antonio

2011-01-01

The excursion set theory, where density perturbations evolve stochastically with the smoothing scale, provides a method for computing the dark matter halo mass function. The computation of the mass function is mapped into the so-called first-passage time problem in the presence of a moving barrier. The excursion set theory is also a powerful formalism to study other properties of dark matter halos such as halo bias, accretion rate, formation time, merging rate and the formation history of halos. This is achieved by computing conditional probabilities with non-trivial initial conditions, and the conditional two-barrier first-crossing rate. In this paper we use the recently-developed path integral formulation of the excursion set theory to calculate analytically these conditional probabilities in the presence of a generic moving barrier, including the one describing the ellipsoidal collapse, and for both Gaussian and non-Gaussian initial conditions. The non-Markovianity of the random walks induced by non-Gaussi...

Transformation & uncertainty : some thoughts on quantum probability theory, quantum statistics, and natural bundles

NARCIS (Netherlands)

Janssens, B.

2010-01-01

This PHD thesis is concerned partly with uncertainty relations in quantum probability theory, partly with state estimation in quantum stochastics, and partly with natural bundles in differential geometry. The laws of quantum mechanics impose severe restrictions on the performance of measurement.

Accurate step-hold tracking of smoothly varying periodic and aperiodic probability.

Science.gov (United States)

Ricci, Matthew; Gallistel, Randy

2017-07-01

Subjects observing many samples from a Bernoulli distribution are able to perceive an estimate of the generating parameter. A question of fundamental importance is how the current percept-what we think the probability now is-depends on the sequence of observed samples. Answers to this question are strongly constrained by the manner in which the current percept changes in response to changes in the hidden parameter. Subjects do not update their percept trial-by-trial when the hidden probability undergoes unpredictable and unsignaled step changes; instead, they update it only intermittently in a step-hold pattern. It could be that the step-hold pattern is not essential to the perception of probability and is only an artifact of step changes in the hidden parameter. However, we now report that the step-hold pattern obtains even when the parameter varies slowly and smoothly. It obtains even when the smooth variation is periodic (sinusoidal) and perceived as such. We elaborate on a previously published theory that accounts for: (i) the quantitative properties of the step-hold update pattern; (ii) subjects' quick and accurate reporting of changes; (iii) subjects' second thoughts about previously reported changes; (iv) subjects' detection of higher-order structure in patterns of change. We also call attention to the challenges these results pose for trial-by-trial updating theories.

The golden mean in the topology of four-manifolds, in conformal field theory, in the mathematical probability theory and in Cantorian space-time

International Nuclear Information System (INIS)

Marek-Crnjac, L.

2006-01-01

In the present work we show the connections between the topology of four-manifolds, conformal field theory, the mathematical probability theory and Cantorian space-time. In all these different mathematical fields, we find as the main connection the appearance of the golden mean

A theory of Bayesian decision making

OpenAIRE

Karni, Edi

2009-01-01

This paper presents a complete, choice-based, axiomatic Bayesian decision theory. It introduces a new choice set consisting of information-contingent plans for choosing actions and bets and subjective expected utility model with effect-dependent utility functions and action-dependent subjective probabilities which, in conjunction with the updating of the probabilities using Bayes’ rule, gives rise to a unique prior and a set of action-dependent posterior probabilities representing the decisio...

Subjective Expected Utility Theory with "Small Worlds"

DEFF Research Database (Denmark)

Gyntelberg, Jacob; Hansen, Frank

which is a more general construction than a state space. We retain preference axioms similar in spirit to the Savage axioms and obtain, without abandoning linearity of expectations, a subjective expected utility theory which allows for an intuitive distinction between risk and uncertainty. We also...

Beta-decay rate and beta-delayed neutron emission probability of improved gross theory

Science.gov (United States)

Koura, Hiroyuki

2014-09-01

A theoretical study has been carried out on beta-decay rate and beta-delayed neutron emission probability. The gross theory of the beta decay is based on an idea of the sum rule of the beta-decay strength function, and has succeeded in describing beta-decay half-lives of nuclei overall nuclear mass region. The gross theory includes not only the allowed transition as the Fermi and the Gamow-Teller, but also the first-forbidden transition. In this work, some improvements are introduced as the nuclear shell correction on nuclear level densities and the nuclear deformation for nuclear strength functions, those effects were not included in the original gross theory. The shell energy and the nuclear deformation for unmeasured nuclei are adopted from the KTUY nuclear mass formula, which is based on the spherical-basis method. Considering the properties of the integrated Fermi function, we can roughly categorized energy region of excited-state of a daughter nucleus into three regions: a highly-excited energy region, which fully affect a delayed neutron probability, a middle energy region, which is estimated to contribute the decay heat, and a region neighboring the ground-state, which determines the beta-decay rate. Some results will be given in the presentation. A theoretical study has been carried out on beta-decay rate and beta-delayed neutron emission probability. The gross theory of the beta decay is based on an idea of the sum rule of the beta-decay strength function, and has succeeded in describing beta-decay half-lives of nuclei overall nuclear mass region. The gross theory includes not only the allowed transition as the Fermi and the Gamow-Teller, but also the first-forbidden transition. In this work, some improvements are introduced as the nuclear shell correction on nuclear level densities and the nuclear deformation for nuclear strength functions, those effects were not included in the original gross theory. The shell energy and the nuclear deformation for

Sensitivity and bias in decision-making under risk: evaluating the perception of reward, its probability and value.

Directory of Open Access Journals (Sweden)

Madeleine E Sharp

Full Text Available BACKGROUND: There are few clinical tools that assess decision-making under risk. Tests that characterize sensitivity and bias in decisions between prospects varying in magnitude and probability of gain may provide insights in conditions with anomalous reward-related behaviour. OBJECTIVE: We designed a simple test of how subjects integrate information about the magnitude and the probability of reward, which can determine discriminative thresholds and choice bias in decisions under risk. DESIGN/METHODS: Twenty subjects were required to choose between two explicitly described prospects, one with higher probability but lower magnitude of reward than the other, with the difference in expected value between the two prospects varying from 3 to 23%. RESULTS: Subjects showed a mean threshold sensitivity of 43% difference in expected value. Regarding choice bias, there was a 'risk premium' of 38%, indicating a tendency to choose higher probability over higher reward. An analysis using prospect theory showed that this risk premium is the predicted outcome of hypothesized non-linearities in the subjective perception of reward value and probability. CONCLUSIONS: This simple test provides a robust measure of discriminative value thresholds and biases in decisions under risk. Prospect theory can also make predictions about decisions when subjective perception of reward or probability is anomalous, as may occur in populations with dopaminergic or striatal dysfunction, such as Parkinson's disease and schizophrenia.

Sensitivity and Bias in Decision-Making under Risk: Evaluating the Perception of Reward, Its Probability and Value

Science.gov (United States)

Sharp, Madeleine E.; Viswanathan, Jayalakshmi; Lanyon, Linda J.; Barton, Jason J. S.

2012-01-01

Background There are few clinical tools that assess decision-making under risk. Tests that characterize sensitivity and bias in decisions between prospects varying in magnitude and probability of gain may provide insights in conditions with anomalous reward-related behaviour. Objective We designed a simple test of how subjects integrate information about the magnitude and the probability of reward, which can determine discriminative thresholds and choice bias in decisions under risk. Design/Methods Twenty subjects were required to choose between two explicitly described prospects, one with higher probability but lower magnitude of reward than the other, with the difference in expected value between the two prospects varying from 3 to 23%. Results Subjects showed a mean threshold sensitivity of 43% difference in expected value. Regarding choice bias, there was a ‘risk premium’ of 38%, indicating a tendency to choose higher probability over higher reward. An analysis using prospect theory showed that this risk premium is the predicted outcome of hypothesized non-linearities in the subjective perception of reward value and probability. Conclusions This simple test provides a robust measure of discriminative value thresholds and biases in decisions under risk. Prospect theory can also make predictions about decisions when subjective perception of reward or probability is anomalous, as may occur in populations with dopaminergic or striatal dysfunction, such as Parkinson's disease and schizophrenia. PMID:22493669

Uncertainty theory

CERN Document Server

Liu, Baoding

2015-01-01

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case. In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees. This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, c...

Dangerous "spin": the probability myth of evidence-based prescribing - a Merleau-Pontyian approach.

Science.gov (United States)

Morstyn, Ron

2011-08-01

The aim of this study was to examine logical positivist statistical probability statements used to support and justify "evidence-based" prescribing rules in psychiatry when viewed from the major philosophical theories of probability, and to propose "phenomenological probability" based on Maurice Merleau-Ponty's philosophy of "phenomenological positivism" as a better clinical and ethical basis for psychiatric prescribing. The logical positivist statistical probability statements which are currently used to support "evidence-based" prescribing rules in psychiatry have little clinical or ethical justification when subjected to critical analysis from any of the major theories of probability and represent dangerous "spin" because they necessarily exclude the individual , intersubjective and ambiguous meaning of mental illness. A concept of "phenomenological probability" founded on Merleau-Ponty's philosophy of "phenomenological positivism" overcomes the clinically destructive "objectivist" and "subjectivist" consequences of logical positivist statistical probability and allows psychopharmacological treatments to be appropriately integrated into psychiatric treatment.

Concepts of probability theory

CERN Document Server

Pfeiffer, Paul E

1979-01-01

Using the Kolmogorov model, this intermediate-level text discusses random variables, probability distributions, mathematical expectation, random processes, more. For advanced undergraduates students of science, engineering, or math. Includes problems with answers and six appendixes. 1965 edition.

Probability of primordial black hole pair creation in a modified gravitational theory

International Nuclear Information System (INIS)

Paul, B. C.; Paul, Dilip

2006-01-01

We compute the probability for quantum creation of an inflationary universe with and without a pair of black holes in a modified gravity. The action of the modified theory of gravity contains αR 2 and δR -1 terms in addition to a cosmological constant (Λ) in the Einstein-Hilbert action. The probabilities for the creation of universe with a pair of black holes have been evaluated considering two different kinds of spatial sections, one which accommodates a pair of black holes and the other without black hole. We adopt a technique prescribed by Bousso and Hawking to calculate the above creation probability in a semiclassical approximation using the Hartle-Hawking boundary condition. We note a class of new and physically interesting instanton solutions characterized by the parameters in the action. These instantons may play an important role in the creation of the early universe. We also note that the probability of creation of a universe with a pair of black holes is strongly suppressed with a positive cosmological constant when δ=(4Λ 2 /3) for α>0 but it is more probable for α<-(1/6Λ). In the modified gravity considered here instanton solutions are permitted even without a cosmological constant when one begins with a negative δ

Probabilities and Possibilities: The Strategic Counseling Implications of the Chaos Theory of Careers

Science.gov (United States)

Pryor, Robert G. L.; Amundson, Norman E.; Bright, Jim E. H.

2008-01-01

The chaos theory of careers emphasizes both stability and change in its account of career development. This article outlines counseling strategies derived from this emphasis in terms of convergent or probability thinking and emergent or possibility thinking. These 2 perspectives are characterized, and practical counseling strategy implications are…

A Complete Theory of Everything (Will Be Subjective

Directory of Open Access Journals (Sweden)

Marcus Hutter

2010-09-01

Full Text Available Increasingly encompassing models have been suggested for our world. Theories range from generally accepted to increasingly speculative to apparently bogus. The progression of theories from ego- to geo- to helio-centric models to universe and multiverse theories and beyond was accompanied by a dramatic increase in the sizes of the postulated worlds, with humans being expelled from their center to ever more remote and random locations. Rather than leading to a true theory of everything, this trend faces a turning point after which the predictive power of such theories decreases (actually to zero. Incorporating the location and other capacities of the observer into such theories avoids this problem and allows to distinguish meaningful from predictively meaningless theories. This also leads to a truly complete theory of everything consisting of a (conventional objective theory of everything plus a (novel subjective observer process. The observer localization is neither based on the controversial anthropic principle, nor has it anything to do with the quantum-mechanical observation process. The suggested principle is extended to more practical (partial, approximate, probabilistic, parametric world models (rather than theories of everything. Finally, I provide a justification of Ockham’s razor, and criticize the anthropic principle, the doomsday argument, the no free lunch theorem, and the falsifiability dogma.

Contribution to the neutronic theory of random stacks (diffusion coefficient and first-flight collision probabilities) with a general theorem on collision probabilities

International Nuclear Information System (INIS)

Dixmier, Marc.

1980-10-01

A general expression of the diffusion coefficient (d.c.) of neutrons was given, with stress being put on symmetries. A system of first-flight collision probabilities for the case of a random stack of any number of types of one- and two-zoned spherical pebbles, with an albedo at the frontiers of the elements or (either) consideration of the interstital medium, was built; to that end, the bases of collision probability theory were reviewed, and a wide generalisation of the reciprocity theorem for those probabilities was demonstrated. The migration area of neutrons was expressed for any random stack of convex, 'simple' and 'regular-contact' elements, taking into account the correlations between free-paths; the average cosinus of re-emission of neutrons by an element, in the case of a homogeneous spherical pebble and the transport approximation, was expressed; the superiority of the so-found result over Behrens' theory, for the type of media under consideration, was established. The 'fine structure current term' of the d.c. was also expressed, and it was shown that its 'polarisation term' is negligible. Numerical applications showed that the global heterogeneity effect on the d.c. of pebble-bed reactors is comparable with that for Graphite-moderated, Carbon gas-cooled, natural Uranium reactors. The code CARACOLE, which integrates all the results here obtained, was introduced [fr

Probable Inference and Quantum Mechanics

International Nuclear Information System (INIS)

Grandy, W. T. Jr.

2009-01-01

In its current very successful interpretation the quantum theory is fundamentally statistical in nature. Although commonly viewed as a probability amplitude whose (complex) square is a probability, the wavefunction or state vector continues to defy consensus as to its exact meaning, primarily because it is not a physical observable. Rather than approach this problem directly, it is suggested that it is first necessary to clarify the precise role of probability theory in quantum mechanics, either as applied to, or as an intrinsic part of the quantum theory. When all is said and done the unsurprising conclusion is that quantum mechanics does not constitute a logic and probability unto itself, but adheres to the long-established rules of classical probability theory while providing a means within itself for calculating the relevant probabilities. In addition, the wavefunction is seen to be a description of the quantum state assigned by an observer based on definite information, such that the same state must be assigned by any other observer based on the same information, in much the same way that probabilities are assigned.

Elapsed decision time affects the weighting of prior probability in a perceptual decision task

Science.gov (United States)

Hanks, Timothy D.; Mazurek, Mark E.; Kiani, Roozbeh; Hopp, Elizabeth; Shadlen, Michael N.

2012-01-01

Decisions are often based on a combination of new evidence with prior knowledge of the probable best choice. Optimal combination requires knowledge about the reliability of evidence, but in many realistic situations, this is unknown. Here we propose and test a novel theory: the brain exploits elapsed time during decision formation to combine sensory evidence with prior probability. Elapsed time is useful because (i) decisions that linger tend to arise from less reliable evidence, and (ii) the expected accuracy at a given decision time depends on the reliability of the evidence gathered up to that point. These regularities allow the brain to combine prior information with sensory evidence by weighting the latter in accordance with reliability. To test this theory, we manipulated the prior probability of the rewarded choice while subjects performed a reaction-time discrimination of motion direction using a range of stimulus reliabilities that varied from trial to trial. The theory explains the effect of prior probability on choice and reaction time over a wide range of stimulus strengths. We found that prior probability was incorporated into the decision process as a dynamic bias signal that increases as a function of decision time. This bias signal depends on the speed-accuracy setting of human subjects, and it is reflected in the firing rates of neurons in the lateral intraparietal cortex (LIP) of rhesus monkeys performing this task. PMID:21525274

Subjective probability appraisal of uranium resources in the state of New Mexico

International Nuclear Information System (INIS)

Ellis, J.R.; Harris, D.P.; VanWie, N.H.

1975-12-01

This report presents an estimate of undiscovered uranium resources in New Mexico of 226,681,000 tons of material containing 455,480 tons U 3 O 8 . The basis for this estimate was a survey of expectations of 36 geologists, in terms of subjective probabilities of number of deposits, ore tonnage, and grade. Weighting of the geologists' estimates to derive a mean value used a self-appraisal index of their knowledge within the field. Detailed estimates are presented for the state, for each of 62 subdivisions (cells), and for an aggregation of eight cells encompassing the San Juan Basin, which is estimated to contain 92 percent of the undiscovered uranium resources in New Mexico. Ore-body attributes stated as probability distributions enabled the application of Monte Carlo methods to the analysis of the data. Sampling of estimates of material and contained U 3 O 8 which are provided as probability distributions indicates a 10 percent probability of there being at least 600,000 tons U 3 O 8 remaining undiscovered in deposits virtually certain to number between 500 and 565. An indicated probability of 99.5 percent that the ore grade is greater than 0.12 percent U 3 O 8 suggests that this survey may not provide reliable estimates of the abundance of material in very low-grade categories. Extrapolation to examine the potential for such deposits indicates more than 1,000,000 tons U 3 O 8 may be available down to a grade of 0.05 percent U 3 O 8 . Supplemental point estimates of ore depth and thickness allowed derivative estimates of cost of development, extraction, and milling. 80 percent of the U 3 O 8 is estimated to be available at a cost less than dollars 15/lb (1974) and about 98 percent at less than dollars 30/lb

Modeling self on others: An import theory of subjectivity and selfhood.

Science.gov (United States)

Prinz, Wolfgang

2017-03-01

This paper outlines an Import Theory of subjectivity and selfhood. Import theory claims that subjectivity is initially perceived as a key feature of other minds before it then becomes imported from other minds to own minds whereby it lays the ground for mental selfhood. Import theory builds on perception-production matching, which in turn draws on both representational mechanisms and social practices. Representational mechanisms rely on common coding of perception and production. Social practices rely on action mirroring in dyadic interactions. The interplay between mechanisms and practices gives rise to model self on others. Individuals become intentional agents in virtue of perceiving others mirroring themselves. The outline of the theory is preceded by an introductory section that locates import theory in the broader context of competing approaches, and it is followed by a concluding section that assesses import theory in terms of empirical evidence and explanatory power. Copyright © 2017 Elsevier Inc. All rights reserved.

The use of modern information technologies in teaching students of economics theory of probability

Directory of Open Access Journals (Sweden)

Иван Васильевич Детушев

2013-12-01

Full Text Available This article discusses the use of the program «MathCAD» in teaching students of economic specialties of mathematics. It is shown that the use of this software product contributes to the effective development of methods for solving problems of the theory of probability.

On possibility of agreement of quantum mechanics with classical probability theory

International Nuclear Information System (INIS)

Slavnov, D.A.

2006-01-01

Paper describes a scheme to carry out a construction of the quantum mechanics where the quantum system is assumed to be a pattern of the open classical subsystems. It enables to make use both of the formal classical logic and the classical probability theory in the quantum mechanics. On the other hand, in terms of the mentioned approach one manages to ensure complete reconstruction of the quantum mechanics standard mathematical tool specifying its application limits. The problem dealing with the quantum state reduction is scrutinized [ru

Subjective expected utility without preferences

OpenAIRE

Bouyssou , Denis; Marchant , Thierry

2011-01-01

This paper proposes a theory of subjective expected utility based on primitives only involving the fact that an act can be judged either "attractive" or "unattractive". We give conditions implying that there are a utility function on the set of consequences and a probability distribution on the set of states such that attractive acts have a subjective expected utility above some threshold. The numerical representation that is obtained has strong uniqueness properties.

Linear positivity and virtual probability

International Nuclear Information System (INIS)

Hartle, James B.

2004-01-01

We investigate the quantum theory of closed systems based on the linear positivity decoherence condition of Goldstein and Page. The objective of any quantum theory of a closed system, most generally the universe, is the prediction of probabilities for the individual members of sets of alternative coarse-grained histories of the system. Quantum interference between members of a set of alternative histories is an obstacle to assigning probabilities that are consistent with the rules of probability theory. A quantum theory of closed systems therefore requires two elements: (1) a condition specifying which sets of histories may be assigned probabilities and (2) a rule for those probabilities. The linear positivity condition of Goldstein and Page is the weakest of the general conditions proposed so far. Its general properties relating to exact probability sum rules, time neutrality, and conservation laws are explored. Its inconsistency with the usual notion of independent subsystems in quantum mechanics is reviewed. Its relation to the stronger condition of medium decoherence necessary for classicality is discussed. The linear positivity of histories in a number of simple model systems is investigated with the aim of exhibiting linearly positive sets of histories that are not decoherent. The utility of extending the notion of probability to include values outside the range of 0-1 is described. Alternatives with such virtual probabilities cannot be measured or recorded, but can be used in the intermediate steps of calculations of real probabilities. Extended probabilities give a simple and general way of formulating quantum theory. The various decoherence conditions are compared in terms of their utility for characterizing classicality and the role they might play in further generalizations of quantum mechanics

Psychophysics of the probability weighting function

Science.gov (United States)

Takahashi, Taiki

2011-03-01

A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) [4] axiomatically derived the probability weighting function w(p)=exp(-() (01e)=1e,w(1)=1), which has extensively been studied in behavioral neuroeconomics. The present study utilizes psychophysical theory to derive Prelec's probability weighting function from psychophysical laws of perceived waiting time in probabilistic choices. Also, the relations between the parameters in the probability weighting function and the probability discounting function in behavioral psychology are derived. Future directions in the application of the psychophysical theory of the probability weighting function in econophysics and neuroeconomics are discussed.

Invariant probabilities of transition functions

CERN Document Server

Zaharopol, Radu

2014-01-01

The structure of the set of all the invariant probabilities and the structure of various types of individual invariant probabilities of a transition function are two topics of significant interest in the theory of transition functions, and are studied in this book. The results obtained are useful in ergodic theory and the theory of dynamical systems, which, in turn, can be applied in various other areas (like number theory). They are illustrated using transition functions defined by flows, semiflows, and one-parameter convolution semigroups of probability measures. In this book, all results on transition probabilities that have been published by the author between 2004 and 2008 are extended to transition functions. The proofs of the results obtained are new. For transition functions that satisfy very general conditions the book describes an ergodic decomposition that provides relevant information on the structure of the corresponding set of invariant probabilities. Ergodic decomposition means a splitting of t...

Representing Uncertainty by Probability and Possibility

DEFF Research Database (Denmark)

of uncertain parameters. Monte Carlo simulation is readily used for practical calculations. However, an alternative approach is offered by possibility theory making use of possibility distributions such as intervals and fuzzy intervals. This approach is well suited to represent lack of knowledge or imprecision......Uncertain parameters in modeling are usually represented by probability distributions reflecting either the objective uncertainty of the parameters or the subjective belief held by the model builder. This approach is particularly suited for representing the statistical nature or variance...

Representation theory of finite monoids

CERN Document Server

Steinberg, Benjamin

2016-01-01

This first text on the subject provides a comprehensive introduction to the representation theory of finite monoids. Carefully worked examples and exercises provide the bells and whistles for graduate accessibility, bringing a broad range of advanced readers to the forefront of research in the area. Highlights of the text include applications to probability theory, symbolic dynamics, and automata theory. Comfort with module theory, a familiarity with ordinary group representation theory, and the basics of Wedderburn theory, are prerequisites for advanced graduate level study. Researchers in algebra, algebraic combinatorics, automata theory, and probability theory, will find this text enriching with its thorough presentation of applications of the theory to these fields. Prior knowledge of semigroup theory is not expected for the diverse readership that may benefit from this exposition. The approach taken in this book is highly module-theoretic and follows the modern flavor of the theory of finite dimensional ...

Probability elements of the mathematical theory

CERN Document Server

Heathcote, C R

2000-01-01

Designed for students studying mathematical statistics and probability after completing a course in calculus and real variables, this text deals with basic notions of probability spaces, random variables, distribution functions and generating functions, as well as joint distributions and the convergence properties of sequences of random variables. Includes worked examples and over 250 exercises with solutions.

Free probability and random matrices

CERN Document Server

Mingo, James A

2017-01-01

This volume opens the world of free probability to a wide variety of readers. From its roots in the theory of operator algebras, free probability has intertwined with non-crossing partitions, random matrices, applications in wireless communications, representation theory of large groups, quantum groups, the invariant subspace problem, large deviations, subfactors, and beyond. This book puts a special emphasis on the relation of free probability to random matrices, but also touches upon the operator algebraic, combinatorial, and analytic aspects of the theory. The book serves as a combination textbook/research monograph, with self-contained chapters, exercises scattered throughout the text, and coverage of important ongoing progress of the theory. It will appeal to graduate students and all mathematicians interested in random matrices and free probability from the point of view of operator algebras, combinatorics, analytic functions, or applications in engineering and statistical physics.

A philosophical essay on probabilities

CERN Document Server

Laplace, Marquis de

1996-01-01

A classic of science, this famous essay by ""the Newton of France"" introduces lay readers to the concepts and uses of probability theory. It is of especial interest today as an application of mathematical techniques to problems in social and biological sciences.Generally recognized as the founder of the modern phase of probability theory, Laplace here applies the principles and general results of his theory ""to the most important questions of life, which are, in effect, for the most part, problems in probability."" Thus, without the use of higher mathematics, he demonstrates the application

What subject matter questions motivate the use of machine learning approaches compared to statistical models for probability prediction?

Science.gov (United States)

Binder, Harald

2014-07-01

This is a discussion of the following papers: "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory" by Jochen Kruppa, Yufeng Liu, Gérard Biau, Michael Kohler, Inke R. König, James D. Malley, and Andreas Ziegler; and "Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications" by Jochen Kruppa, Yufeng Liu, Hans-Christian Diener, Theresa Holste, Christian Weimar, Inke R. König, and Andreas Ziegler. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Facilitating Group Decision-Making: Facilitator's Subjective Theories on Group Coordination

Directory of Open Access Journals (Sweden)

Michaela Kolbe

2008-10-01

Full Text Available A key feature of group facilitation is motivating and coordinating people to perform their joint work. This paper focuses on group coordination which is a prerequisite to group effectiveness, especially in complex tasks. Decision-making in groups is a complex task that consequently needs to be coordinated by explicit rather than implicit coordination mechanisms. Based on the embedded definition that explicit coordination does not just happen but is purposely executed by individuals, we argue that individual coordination intentions and mechanisms should be taken into account. Thus far, the subjective perspective of coordination has been neglected in coordination theory, which is understandable given the difficulties in defining and measuring subjective aspects of group facilitation. We therefore conducted focused interviews with eight experts who either worked as senior managers or as experienced group facilitators and analysed their approaches to group coordination using methods of content analysis. Results show that these experts possess sophisticated mental representations of their coordination behaviour. These subjective coordination theories can be organised in terms of coordination schemes in which coordination-releasing situations are facilitated by special coordination mechanisms that, in turn, lead to the perception of specific consequences. We discuss the importance of these subjective coordination theories for effectively facilitating group decision-making and minimising process losses. URN: urn:nbn:de:0114-fqs0901287

Scaling Qualitative Probability

OpenAIRE

Burgin, Mark

2017-01-01

There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability structures and is more coherent than existing approaches. This setting makes it possible proving that any comparative probability is induced by some probability structure (Theorem 2.1), that classical probability is a probability structure (Theorem 2.2) and that i...

COVAL, Compound Probability Distribution for Function of Probability Distribution

International Nuclear Information System (INIS)

Astolfi, M.; Elbaz, J.

1979-01-01

1 - Nature of the physical problem solved: Computation of the probability distribution of a function of variables, given the probability distribution of the variables themselves. 'COVAL' has been applied to reliability analysis of a structure subject to random loads. 2 - Method of solution: Numerical transformation of probability distributions

Expected utility with lower probabilities

DEFF Research Database (Denmark)

Hendon, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

1994-01-01

An uncertain and not just risky situation may be modeled using so-called belief functions assigning lower probabilities to subsets of outcomes. In this article we extend the von Neumann-Morgenstern expected utility theory from probability measures to belief functions. We use this theory...

Traceable accounts of subjective probability judgments in the IPCC and beyond

Science.gov (United States)

Baer, P. G.

2012-12-01

One of the major sources of controversy surrounding the reports of the IPCC has been the characterization of uncertainty. Although arguably the IPCC has paid more attention to the process of uncertainty analysis and communication than any comparable assessment body, its efforts to achieve consistency have produced mixed results. In particular, the extensive use of subjective probability assessment has attracted widespread criticism. Statements such as "Average Northern Hemisphere temperatures during the second half of the 20th century were very likely higher than during any other 50-year period in the last 500 years" are ubiquitous (one online database lists nearly 3000 such claims), and indeed are the primary way in which its key "findings" are reported. Much attention is drawn to the precise quantitative definition of such statements (e.g., "very likely" means >90% probability, vs. "extremely likely" which means >95% certainty). But there is no process by which the decision regarding the choice of such uncertainty level for a given finding is formally made or reported, and thus they are easily by disputed by anyone, expert or otherwise, who disagrees with the assessment. In the "Uncertainty Guidance Paper" for the Third Assessment Report, Richard Moss and Steve Schneider defined the concept of a "traceable account," which gave exhaustive detail regarding how one ought to provide documentation of such an uncertainty assessment. But the guidance, while appearing straightforward and reasonable, in fact was an unworkable recipe, which would have taken near-infinite time if used for more than a few key results, and would have required a different structuring of the text than the conventional scientific assessment. And even then it would have left a gap when it came to the actual provenance of any such specific judgments, because there simply is no formal step at which individuals turn their knowledge of the evidence on some finding into a probability judgment. The

Dependence in probabilistic modeling Dempster-Shafer theory and probability bounds analysis

Energy Technology Data Exchange (ETDEWEB)

Ferson, Scott [Applied Biomathematics, Setauket, NY (United States); Nelsen, Roger B. [Lewis & Clark College, Portland OR (United States); Hajagos, Janos [Applied Biomathematics, Setauket, NY (United States); Berleant, Daniel J. [Iowa State Univ., Ames, IA (United States); Zhang, Jianzhong [Iowa State Univ., Ames, IA (United States); Tucker, W. Troy [Applied Biomathematics, Setauket, NY (United States); Ginzburg, Lev R. [Applied Biomathematics, Setauket, NY (United States); Oberkampf, William L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-05-01

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

Science.gov (United States)

Wei, Wei; Larrey-Lassalle, Pyrène; Faure, Thierry; Dumoulin, Nicolas; Roux, Philippe; Mathias, Jean-Denis

2016-03-01

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

Upgrading Probability via Fractions of Events

Directory of Open Access Journals (Sweden)

Frič Roman

2016-08-01

Full Text Available The influence of “Grundbegriffe” by A. N. Kolmogorov (published in 1933 on education in the area of probability and its impact on research in stochastics cannot be overestimated. We would like to point out three aspects of the classical probability theory “calling for” an upgrade: (i classical random events are black-and-white (Boolean; (ii classical random variables do not model quantum phenomena; (iii basic maps (probability measures and observables { dual maps to random variables have very different “mathematical nature”. Accordingly, we propose an upgraded probability theory based on Łukasiewicz operations (multivalued logic on events, elementary category theory, and covering the classical probability theory as a special case. The upgrade can be compared to replacing calculations with integers by calculations with rational (and real numbers. Namely, to avoid the three objections, we embed the classical (Boolean random events (represented by the f0; 1g-valued indicator functions of sets into upgraded random events (represented by measurable {0; 1}-valued functions, the minimal domain of probability containing “fractions” of classical random events, and we upgrade the notions of probability measure and random variable.

Estimation of delayed neutron emission probability by using the gross theory of nuclear β-decay

International Nuclear Information System (INIS)

Tachibana, Takahiro

1999-01-01

The delayed neutron emission probabilities (P n -values) of fission products are necessary in the study of reactor physics; e.g. in the calculation of total delayed neutron yields and in the summation calculation of decay heat. In this report, the P n -values estimated by the gross theory for some fission products are compared with experiment, and it is found that, on the average, the semi-gross theory somewhat underestimates the experimental P n -values. A modification of the β-decay strength function is briefly discussed to get more reasonable P n -values. (author)

Probability tales

CERN Document Server

Grinstead, Charles M; Snell, J Laurie

2011-01-01

This book explores four real-world topics through the lens of probability theory. It can be used to supplement a standard text in probability or statistics. Most elementary textbooks present the basic theory and then illustrate the ideas with some neatly packaged examples. Here the authors assume that the reader has seen, or is learning, the basic theory from another book and concentrate in some depth on the following topics: streaks, the stock market, lotteries, and fingerprints. This extended format allows the authors to present multiple approaches to problems and to pursue promising side discussions in ways that would not be possible in a book constrained to cover a fixed set of topics. To keep the main narrative accessible, the authors have placed the more technical mathematical details in appendices. The appendices can be understood by someone who has taken one or two semesters of calculus.

Handbook of probability

CERN Document Server

Florescu, Ionut

2013-01-01

THE COMPLETE COLLECTION NECESSARY FOR A CONCRETE UNDERSTANDING OF PROBABILITY Written in a clear, accessible, and comprehensive manner, the Handbook of Probability presents the fundamentals of probability with an emphasis on the balance of theory, application, and methodology. Utilizing basic examples throughout, the handbook expertly transitions between concepts and practice to allow readers an inclusive introduction to the field of probability. The book provides a useful format with self-contained chapters, allowing the reader easy and quick reference. Each chapter includes an introductio

Probability in quantum mechanics

Directory of Open Access Journals (Sweden)

J. G. Gilson

1982-01-01

Full Text Available By using a fluid theory which is an alternative to quantum theory but from which the latter can be deduced exactly, the long-standing problem of how quantum mechanics is related to stochastic processes is studied. It can be seen how the Schrödinger probability density has a relationship to time spent on small sections of an orbit, just as the probability density has in some classical contexts.

Subjective Vertical Conflict Theory and Space Motion Sickness.

Science.gov (United States)

Chen, Wei; Chao, Jian-Gang; Wang, Jin-Kun; Chen, Xue-Wen; Tan, Cheng

2016-02-01

Space motion sickness (SMS) remains a troublesome problem during spaceflight. The subjective vertical (SV) conflict theory postulates that all motion sickness provoking situations are characterized by a condition in which the SV sensed from gravity and visual and idiotropic cues differs from the expected vertical. This theory has been successfully used to predict motion sickness in different vehicles on Earth. We have summarized the most outstanding and recent studies on the illusions and characteristics associated with spatial disorientation and SMS during weightlessness, such as cognitive map and mental rotation, the visual reorientation and inversion illusions, and orientation preferences between visual scenes and the internal z-axis of the body. The relationships between the SV and the incidence of and susceptibility to SMS as well as spatial disorientation were addressed. A consistent framework was presented to understand and explain SMS characteristics in more detail on the basis of the SV conflict theory, which is expected to be more advantageous in SMS prediction, prevention, and training.

Lady luck the theory of probability

CERN Document Server

Weaver, Warren

1982-01-01

""Should I take my umbrella?"" ""Should I buy insurance?"" ""Which horse should I bet on?"" Every day ― in business, in love affairs, in forecasting the weather or the stock market questions arise which cannot be answered by a simple ""yes"" or ""no."" Many of these questions involve probability. Probabilistic thinking is as crucially important in ordinary affairs as it is in the most abstruse realms of science. This book is the best nontechnical introduction to probability ever written. Its author, the late Dr. Warren Weaver, was a professor of mathematics, active in the Rockefeller and Sloa

Introduction to representation theory

CERN Document Server

Etingof, Pavel; Hensel, Sebastian; Liu, Tiankai; Schwendner, Alex

2011-01-01

Very roughly speaking, representation theory studies symmetry in linear spaces. It is a beautiful mathematical subject which has many applications, ranging from number theory and combinatorics to geometry, probability theory, quantum mechanics, and quantum field theory. The goal of this book is to give a "holistic" introduction to representation theory, presenting it as a unified subject which studies representations of associative algebras and treating the representation theories of groups, Lie algebras, and quivers as special cases. Using this approach, the book covers a number of standard topics in the representation theories of these structures. Theoretical material in the book is supplemented by many problems and exercises which touch upon a lot of additional topics; the more difficult exercises are provided with hints. The book is designed as a textbook for advanced undergraduate and beginning graduate students. It should be accessible to students with a strong background in linear algebra and a basic k...

Algebraic and stochastic coding theory

CERN Document Server

Kythe, Dave K

2012-01-01

Using a simple yet rigorous approach, Algebraic and Stochastic Coding Theory makes the subject of coding theory easy to understand for readers with a thorough knowledge of digital arithmetic, Boolean and modern algebra, and probability theory. It explains the underlying principles of coding theory and offers a clear, detailed description of each code. More advanced readers will appreciate its coverage of recent developments in coding theory and stochastic processes. After a brief review of coding history and Boolean algebra, the book introduces linear codes, including Hamming and Golay codes.

F.Y. Edgeworth’s Treatise on Probabilities

OpenAIRE

Alberto Baccini

2007-01-01

Probability theory has a central role in Edgeworth’s thought; this paper examines the philosophical foundation of the theory. Starting from a frequentist position, Edgeworth introduced some innovations on the definition of primitive probabilities. He distinguished between primitive probabilities based on experience of statistical evidence, and primitive a priori probabilities based on a more general and less precise kind of experience, inherited by the human race through evolution. Given prim...

Exact closed form expressions for outage probability of GSC receivers over Rayleigh fading channel subject to self-interference

KAUST Repository

Nam, Sungsik; Hasna, Mazen Omar; Alouini, Mohamed-Slim

2010-01-01

in mind, we capitalize in this paper on some new order statistics results to derive exact closed-form expressions for outage probability of GSC RAKE receivers subject to self-interference over independent and identically distributed Rayleigh fading

From axiomatics of quantum probability to modelling geological uncertainty and management of intelligent hydrocarbon reservoirs with the theory of open quantum systems

Science.gov (United States)

Lozada Aguilar, Miguel Ángel; Khrennikov, Andrei; Oleschko, Klaudia

2018-04-01

As was recently shown by the authors, quantum probability theory can be used for the modelling of the process of decision-making (e.g. probabilistic risk analysis) for macroscopic geophysical structures such as hydrocarbon reservoirs. This approach can be considered as a geophysical realization of Hilbert's programme on axiomatization of statistical models in physics (the famous sixth Hilbert problem). In this conceptual paper, we continue development of this approach to decision-making under uncertainty which is generated by complexity, variability, heterogeneity, anisotropy, as well as the restrictions to accessibility of subsurface structures. The belief state of a geological expert about the potential of exploring a hydrocarbon reservoir is continuously updated by outputs of measurements, and selection of mathematical models and scales of numerical simulation. These outputs can be treated as signals from the information environment E. The dynamics of the belief state can be modelled with the aid of the theory of open quantum systems: a quantum state (representing uncertainty in beliefs) is dynamically modified through coupling with E; stabilization to a steady state determines a decision strategy. In this paper, the process of decision-making about hydrocarbon reservoirs (e.g. `explore or not?'; `open new well or not?'; `contaminated by water or not?'; `double or triple porosity medium?') is modelled by using the Gorini-Kossakowski-Sudarshan-Lindblad equation. In our model, this equation describes the evolution of experts' predictions about a geophysical structure. We proceed with the information approach to quantum theory and the subjective interpretation of quantum probabilities (due to quantum Bayesianism). This article is part of the theme issue `Hilbert's sixth problem'.

From axiomatics of quantum probability to modelling geological uncertainty and management of intelligent hydrocarbon reservoirs with the theory of open quantum systems.

Science.gov (United States)

Lozada Aguilar, Miguel Ángel; Khrennikov, Andrei; Oleschko, Klaudia

2018-04-28

As was recently shown by the authors, quantum probability theory can be used for the modelling of the process of decision-making (e.g. probabilistic risk analysis) for macroscopic geophysical structures such as hydrocarbon reservoirs. This approach can be considered as a geophysical realization of Hilbert's programme on axiomatization of statistical models in physics (the famous sixth Hilbert problem). In this conceptual paper , we continue development of this approach to decision-making under uncertainty which is generated by complexity, variability, heterogeneity, anisotropy, as well as the restrictions to accessibility of subsurface structures. The belief state of a geological expert about the potential of exploring a hydrocarbon reservoir is continuously updated by outputs of measurements, and selection of mathematical models and scales of numerical simulation. These outputs can be treated as signals from the information environment E The dynamics of the belief state can be modelled with the aid of the theory of open quantum systems: a quantum state (representing uncertainty in beliefs) is dynamically modified through coupling with E ; stabilization to a steady state determines a decision strategy. In this paper, the process of decision-making about hydrocarbon reservoirs (e.g. 'explore or not?'; 'open new well or not?'; 'contaminated by water or not?'; 'double or triple porosity medium?') is modelled by using the Gorini-Kossakowski-Sudarshan-Lindblad equation. In our model, this equation describes the evolution of experts' predictions about a geophysical structure. We proceed with the information approach to quantum theory and the subjective interpretation of quantum probabilities (due to quantum Bayesianism).This article is part of the theme issue 'Hilbert's sixth problem'. © 2018 The Author(s).

Contributions to quantum probability

International Nuclear Information System (INIS)

Fritz, Tobias

2010-01-01

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a finite set can occur as the outcome

The enigma of probability and physics

International Nuclear Information System (INIS)

Mayants, L.

1984-01-01

This volume contains a coherent exposition of the elements of two unique sciences: probabilistics (science of probability) and probabilistic physics (application of probabilistics to physics). Proceeding from a key methodological principle, it starts with the disclosure of the true content of probability and the interrelation between probability theory and experimental statistics. This makes is possible to introduce a proper order in all the sciences dealing with probability and, by conceiving the real content of statistical mechanics and quantum mechanics in particular, to construct both as two interconnected domains of probabilistic physics. Consistent theories of kinetics of physical transformations, decay processes, and intramolecular rearrangements are also outlined. The interrelation between the electromagnetic field, photons, and the theoretically discovered subatomic particle 'emon' is considered. Numerous internal imperfections of conventional probability theory, statistical physics, and quantum physics are exposed and removed - quantum physics no longer needs special interpretation. EPR, Bohm, and Bell paradoxes are easily resolved, among others. (Auth.)

The attention schema theory: a mechanistic account of subjective awareness.

Science.gov (United States)

Graziano, Michael S A; Webb, Taylor W

2015-01-01

We recently proposed the attention schema theory, a novel way to explain the brain basis of subjective awareness in a mechanistic and scientifically testable manner. The theory begins with attention, the process by which signals compete for the brain's limited computing resources. This internal signal competition is partly under a bottom-up influence and partly under top-down control. We propose that the top-down control of attention is improved when the brain has access to a simplified model of attention itself. The brain therefore constructs a schematic model of the process of attention, the 'attention schema,' in much the same way that it constructs a schematic model of the body, the 'body schema.' The content of this internal model leads a brain to conclude that it has a subjective experience. One advantage of this theory is that it explains how awareness and attention can sometimes become dissociated; the brain's internal models are never perfect, and sometimes a model becomes dissociated from the object being modeled. A second advantage of this theory is that it explains how we can be aware of both internal and external events. The brain can apply attention to many types of information including external sensory information and internal information about emotions and cognitive states. If awareness is a model of attention, then this model should pertain to the same domains of information to which attention pertains. A third advantage of this theory is that it provides testable predictions. If awareness is the internal model of attention, used to help control attention, then without awareness, attention should still be possible but should suffer deficits in control. In this article, we review the existing literature on the relationship between attention and awareness, and suggest that at least some of the predictions of the theory are borne out by the evidence.

The attention schema theory: a mechanistic account of subjective awareness

Directory of Open Access Journals (Sweden)

Taylor W. Webb

2015-04-01

Full Text Available We recently proposed the attention schema theory, a novel way to explain the brain basis of subjective awareness in a mechanistic and scientifically testable manner. The theory begins with attention, the process by which signals compete for the brain’s limited computing resources. This internal signal competition is partly under a bottom-up influence and partly under top-down control. We propose that the top-down control of attention is improved when the brain has access to a simplified model of attention itself. The brain therefore constructs a schematic model of the process of attention, the ‘attention schema’, in much the same way that it constructs a schematic model of the body, the ‘body schema’. The content of this internal model leads a brain to conclude that it has a subjective experience. One advantage of this theory is that it explains how awareness and attention can sometimes become dissociated; the brain’s internal models are never perfect, and sometimes a model becomes dissociated from the object being modeled. A second advantage of this theory is that it explains how we can be aware of both internal and external events. The brain can apply attention to many types of information including external sensory information and internal information about emotions and cognitive states. If awareness is a model of attention, then this model should pertain to the same domains of information to which attention pertains. A third advantage of this theory is that it provides testable predictions. If awareness is the internal model of attention, used to help control attention, then without awareness, attention should still be possible but should suffer deficits in control. In this article, we review the existing literature on the relationship between attention and awareness, and suggest that at least some of the predictions of the theory are borne out by the evidence.

A modern theory of random variation with applications in stochastic calculus, financial mathematics, and Feynman integration

CERN Document Server

Muldowney, Patrick

2012-01-01

A Modern Theory of Random Variation is a new and radical re-formulation of the mathematical underpinnings of subjects as diverse as investment, communication engineering, and quantum mechanics. Setting aside the classical theory of probability measure spaces, the book utilizes a mathematically rigorous version of the theory of random variation that bases itself exclusively on finitely additive probability distribution functions. In place of twentieth century Lebesgue integration and measure theory, the author uses the simpler concept of Riemann sums, and the non-absolute Riemann-type integration of Henstock. Readers are supplied with an accessible approach to standard elements of probability theory such as the central limmit theorem and Brownian motion as well as remarkable, new results on Feynman diagrams and stochastic integrals. Throughout the book, detailed numerical demonstrations accompany the discussions of abstract mathematical theory, from the simplest elements of the subject to the most complex. I...

Subjective Expected Utility: A Model of Decision-Making.

Science.gov (United States)

Fischoff, Baruch; And Others

1981-01-01

Outlines a model of decision making known to researchers in the field of behavioral decision theory (BDT) as subjective expected utility (SEU). The descriptive and predictive validity of the SEU model, probability and values assessment using SEU, and decision contexts are examined, and a 54-item reference list is provided. (JL)

Introduction to imprecise probabilities

CERN Document Server

Augustin, Thomas; de Cooman, Gert; Troffaes, Matthias C M

2014-01-01

In recent years, the theory has become widely accepted and has been further developed, but a detailed introduction is needed in order to make the material available and accessible to a wide audience. This will be the first book providing such an introduction, covering core theory and recent developments which can be applied to many application areas. All authors of individual chapters are leading researchers on the specific topics, assuring high quality and up-to-date contents. An Introduction to Imprecise Probabilities provides a comprehensive introduction to imprecise probabilities, includin

High-resolution elastic recoil detection utilizing Bayesian probability theory

International Nuclear Information System (INIS)

Neumaier, P.; Dollinger, G.; Bergmaier, A.; Genchev, I.; Goergens, L.; Fischer, R.; Ronning, C.; Hofsaess, H.

2001-01-01

Elastic recoil detection (ERD) analysis is improved in view of depth resolution and the reliability of the measured spectra. Good statistics at even low ion fluences is obtained utilizing a large solid angle of 5 msr at the Munich Q3D magnetic spectrograph and using a 40 MeV 197 Au beam. In this way the elemental depth profiles are not essentially altered during analysis even if distributions with area densities below 1x10 14 atoms/cm 2 are measured. As the energy spread due to the angular acceptance is fully eliminated by ion-optical and numerical corrections, an accurate and reliable apparatus function is derived. It allows to deconvolute the measured spectra using the adaptive kernel method, a maximum entropy concept in the framework of Bayesian probability theory. In addition, the uncertainty of the reconstructed spectra is quantified. The concepts are demonstrated at 13 C depth profiles measured at ultra-thin films of tetrahedral amorphous carbon (ta-C). Depth scales of those profiles are given with an accuracy of 1.4x10 15 atoms/cm 2

Concept of probability in statistical physics

CERN Document Server

Guttmann, Y M

1999-01-01

Foundational issues in statistical mechanics and the more general question of how probability is to be understood in the context of physical theories are both areas that have been neglected by philosophers of physics. This book fills an important gap in the literature by providing a most systematic study of how to interpret probabilistic assertions in the context of statistical mechanics. The book explores both subjectivist and objectivist accounts of probability, and takes full measure of work in the foundations of probability theory, in statistical mechanics, and in mathematical theory. It will be of particular interest to philosophers of science, physicists and mathematicians interested in foundational issues, and also to historians of science.

Paraconsistent Probabilities: Consistency, Contradictions and Bayes’ Theorem

Directory of Open Access Journals (Sweden)

Juliana Bueno-Soler

2016-09-01

Full Text Available This paper represents the first steps towards constructing a paraconsistent theory of probability based on the Logics of Formal Inconsistency (LFIs. We show that LFIs encode very naturally an extension of the notion of probability able to express sophisticated probabilistic reasoning under contradictions employing appropriate notions of conditional probability and paraconsistent updating, via a version of Bayes’ theorem for conditionalization. We argue that the dissimilarity between the notions of inconsistency and contradiction, one of the pillars of LFIs, plays a central role in our extended notion of probability. Some critical historical and conceptual points about probability theory are also reviewed.

Contributions to quantum probability

Energy Technology Data Exchange (ETDEWEB)

Fritz, Tobias

2010-06-25

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a

A Tale of Two Probabilities

Science.gov (United States)

Falk, Ruma; Kendig, Keith

2013-01-01

Two contestants debate the notorious probability problem of the sex of the second child. The conclusions boil down to explication of the underlying scenarios and assumptions. Basic principles of probability theory are highlighted.

Probability functions in the context of signed involutive meadows

NARCIS (Netherlands)

Bergstra, J.A.; Ponse, A.

2016-01-01

The Kolmogorov axioms for probability functions are placed in the context of signed meadows. A completeness theorem is stated and proven for the resulting equational theory of probability calculus. Elementary definitions of probability theory are restated in this framework.

The perception of probability.

Science.gov (United States)

Gallistel, C R; Krishan, Monika; Liu, Ye; Miller, Reilly; Latham, Peter E

2014-01-01

We present a computational model to explain the results from experiments in which subjects estimate the hidden probability parameter of a stepwise nonstationary Bernoulli process outcome by outcome. The model captures the following results qualitatively and quantitatively, with only 2 free parameters: (a) Subjects do not update their estimate after each outcome; they step from one estimate to another at irregular intervals. (b) The joint distribution of step widths and heights cannot be explained on the assumption that a threshold amount of change must be exceeded in order for them to indicate a change in their perception. (c) The mapping of observed probability to the median perceived probability is the identity function over the full range of probabilities. (d) Precision (how close estimates are to the best possible estimate) is good and constant over the full range. (e) Subjects quickly detect substantial changes in the hidden probability parameter. (f) The perceived probability sometimes changes dramatically from one observation to the next. (g) Subjects sometimes have second thoughts about a previous change perception, after observing further outcomes. (h) The frequency with which they perceive changes moves in the direction of the true frequency over sessions. (Explaining this finding requires 2 additional parametric assumptions.) The model treats the perception of the current probability as a by-product of the construction of a compact encoding of the experienced sequence in terms of its change points. It illustrates the why and the how of intermittent Bayesian belief updating and retrospective revision in simple perception. It suggests a reinterpretation of findings in the recent literature on the neurobiology of decision making. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

Science.gov (United States)

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Cognitive-psychology expertise and the calculation of the probability of a wrongful conviction.

Science.gov (United States)

Rouder, Jeffrey N; Wixted, John T; Christenfeld, Nicholas J S

2018-05-08

Cognitive psychologists are familiar with how their expertise in understanding human perception, memory, and decision-making is applicable to the justice system. They may be less familiar with how their expertise in statistical decision-making and their comfort working in noisy real-world environments is just as applicable. Here we show how this expertise in ideal-observer models may be leveraged to calculate the probability of guilt of Gary Leiterman, a man convicted of murder on the basis of DNA evidence. We show by common probability theory that Leiterman is likely a victim of a tragic contamination event rather than a murderer. Making any calculation of the probability of guilt necessarily relies on subjective assumptions. The conclusion about Leiterman's innocence is not overly sensitive to the assumptions-the probability of innocence remains high for a wide range of reasonable assumptions. We note that cognitive psychologists may be well suited to make these calculations because as working scientists they may be comfortable with the role a reasonable degree of subjectivity plays in analysis.

Eliciting Subjective Probability Distributions with Binary Lotteries

DEFF Research Database (Denmark)

Harrison, Glenn W.; Martínez-Correa, Jimmy; Swarthout, J. Todd

2015-01-01

We test in a laboratory experiment the theoretical prediction that risk attitudes have a surprisingly small role in distorting reports from true belief distributions. We find evidence consistent with theory in our experiment....

Probability, Nondeterminism and Concurrency

DEFF Research Database (Denmark)

Varacca, Daniele

Nondeterminism is modelled in domain theory by the notion of a powerdomain, while probability is modelled by that of the probabilistic powerdomain. Some problems arise when we want to combine them in order to model computation in which both nondeterminism and probability are present. In particula...

Quantum processes: probability fluxes, transition probabilities in unit time and vacuum vibrations

International Nuclear Information System (INIS)

Oleinik, V.P.; Arepjev, Ju D.

1989-01-01

Transition probabilities in unit time and probability fluxes are compared in studying the elementary quantum processes -the decay of a bound state under the action of time-varying and constant electric fields. It is shown that the difference between these quantities may be considerable, and so the use of transition probabilities W instead of probability fluxes Π, in calculating the particle fluxes, may lead to serious errors. The quantity W represents the rate of change with time of the population of the energy levels relating partly to the real states and partly to the virtual ones, and it cannot be directly measured in experiment. The vacuum background is shown to be continuously distorted when a perturbation acts on a system. Because of this the viewpoint of an observer on the physical properties of real particles continuously varies with time. This fact is not taken into consideration in the conventional theory of quantum transitions based on using the notion of probability amplitude. As a result, the probability amplitudes lose their physical meaning. All the physical information on quantum dynamics of a system is contained in the mean values of physical quantities. The existence of considerable differences between the quantities W and Π permits one in principle to make a choice of the correct theory of quantum transitions on the basis of experimental data. (author)

Non-equilibrium random matrix theory. Transition probabilities

International Nuclear Information System (INIS)

Pedro, Francisco Gil; Westphal, Alexander

2016-06-01

In this letter we present an analytic method for calculating the transition probability between two random Gaussian matrices with given eigenvalue spectra in the context of Dyson Brownian motion. We show that in the Coulomb gas language, in large N limit, memory of the initial state is preserved in the form of a universal linear potential acting on the eigenvalues. We compute the likelihood of any given transition as a function of time, showing that as memory of the initial state is lost, transition probabilities converge to those of the static ensemble.

Non-equilibrium random matrix theory. Transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Pedro, Francisco Gil [Univ. Autonoma de Madrid (Spain). Dept. de Fisica Teorica; Westphal, Alexander [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany). Gruppe Theorie

2016-06-15

In this letter we present an analytic method for calculating the transition probability between two random Gaussian matrices with given eigenvalue spectra in the context of Dyson Brownian motion. We show that in the Coulomb gas language, in large N limit, memory of the initial state is preserved in the form of a universal linear potential acting on the eigenvalues. We compute the likelihood of any given transition as a function of time, showing that as memory of the initial state is lost, transition probabilities converge to those of the static ensemble.

A first course in probability

CERN Document Server

Ross, Sheldon

2014-01-01

A First Course in Probability, Ninth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary calculus.

[Biometric bases: basic concepts of probability calculation].

Science.gov (United States)

Dinya, E

1998-04-26

The author gives or outline of the basic concepts of probability theory. The bases of the event algebra, definition of the probability, the classical probability model and the random variable are presented.

Explaining participation differentials in Dutch higher education: The impact of subjective success probabilities on level choice and field choice

NARCIS (Netherlands)

Tolsma, J.; Need, A.; Jong, U. de

2010-01-01

In this article we examine whether subjective estimates of success probabilities explain the effect of social origin, sex, and ethnicity on students' choices between different school tracks in Dutch higher education. The educational options analysed differ in level (i.e. university versus

Explaining participation differentials in Dutch higher education : the impact of subjective success probabilities on level choice and field choice

NARCIS (Netherlands)

Tolsma, J.; Need, A.; Jong, U. de

2010-01-01

In this article we examine whether subjective estimates of success probabilities explain the effect of social origin, sex, and ethnicity on students’ choices between different school tracks in Dutch higher education. The educational options analysed differ in level (i.e. university versus

Probability and Measure

CERN Document Server

Billingsley, Patrick

2012-01-01

Praise for the Third Edition "It is, as far as I'm concerned, among the best books in math ever written....if you are a mathematician and want to have the top reference in probability, this is it." (Amazon.com, January 2006) A complete and comprehensive classic in probability and measure theory Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this

Realistic neurons can compute the operations needed by quantum probability theory and other vector symbolic architectures.

Science.gov (United States)

Stewart, Terrence C; Eliasmith, Chris

2013-06-01

Quantum probability (QP) theory can be seen as a type of vector symbolic architecture (VSA): mental states are vectors storing structured information and manipulated using algebraic operations. Furthermore, the operations needed by QP match those in other VSAs. This allows existing biologically realistic neural models to be adapted to provide a mechanistic explanation of the cognitive phenomena described in the target article by Pothos & Busemeyer (P&B).

Decisions under risk in Parkinson's disease: preserved evaluation of probability and magnitude.

Science.gov (United States)

Sharp, Madeleine E; Viswanathan, Jayalakshmi; McKeown, Martin J; Appel-Cresswell, Silke; Stoessl, A Jon; Barton, Jason J S

2013-11-01

Unmedicated Parkinson's disease patients tend to be risk-averse while dopaminergic treatment causes a tendency to take risks. While dopamine agonists may result in clinically apparent impulse control disorders, treatment with levodopa also causes shift in behaviour associated with an enhanced response to rewards. Two important determinants in decision-making are how subjects perceive the magnitude and probability of outcomes. Our objective was to determine if patients with Parkinson's disease on or off levodopa showed differences in their perception of value when making decisions under risk. The Vancouver Gambling task presents subjects with a choice between one prospect with larger outcome and a second with higher probability. Eighteen age-matched controls and eighteen patients with Parkinson's disease before and after levodopa were tested. In the Gain Phase subjects chose between one prospect with higher probability and another with larger reward to maximize their gains. In the Loss Phase, subjects played to minimize their losses. Patients with Parkinson's disease, on or off levodopa, were similar to controls when evaluating gains. However, in the Loss Phase before levodopa, they were more likely to avoid the prospect with lower probability but larger loss, as indicated by the steeper slope of their group psychometric function (t(24) = 2.21, p = 0.04). Modelling with prospect theory suggested that this was attributable to a 28% overestimation of the magnitude of loss, rather than an altered perception of its probability. While pre-medicated patients with Parkinson's disease show risk-aversion for large losses, patients on levodopa have normal perception of magnitude and probability for both loss and gain. The finding of accurate and normally biased decisions under risk in medicated patients with PD is important because it indicates that, if there is indeed anomalous risk-seeking behaviour in such a cohort, it may derive from abnormalities in components of

Probability density function evolution of power systems subject to stochastic variation of renewable energy

Science.gov (United States)

Wei, J. Q.; Cong, Y. C.; Xiao, M. Q.

2018-05-01

As renewable energies are increasingly integrated into power systems, there is increasing interest in stochastic analysis of power systems.Better techniques should be developed to account for the uncertainty caused by penetration of renewables and consequently analyse its impacts on stochastic stability of power systems. In this paper, the Stochastic Differential Equations (SDEs) are used to represent the evolutionary behaviour of the power systems. The stationary Probability Density Function (PDF) solution to SDEs modelling power systems excited by Gaussian white noise is analysed. Subjected to such random excitation, the Joint Probability Density Function (JPDF) solution to the phase angle and angular velocity is governed by the generalized Fokker-Planck-Kolmogorov (FPK) equation. To solve this equation, the numerical method is adopted. Special measure is taken such that the generalized FPK equation is satisfied in the average sense of integration with the assumed PDF. Both weak and strong intensities of the stochastic excitations are considered in a single machine infinite bus power system. The numerical analysis has the same result as the one given by the Monte Carlo simulation. Potential studies on stochastic behaviour of multi-machine power systems with random excitations are discussed at the end.

Independent Events in Elementary Probability Theory

Science.gov (United States)

Csenki, Attila

2011-01-01

In Probability and Statistics taught to mathematicians as a first introduction or to a non-mathematical audience, joint independence of events is introduced by requiring that the multiplication rule is satisfied. The following statement is usually tacitly assumed to hold (and, at best, intuitively motivated): If the n events E[subscript 1],…

Introduction to probability and measure

CERN Document Server

Parthasarathy, K R

2005-01-01

According to a remark attributed to Mark Kac 'Probability Theory is a measure theory with a soul'. This book with its choice of proofs, remarks, examples and exercises has been prepared taking both these aesthetic and practical aspects into account.

The theory, direction, and magnitude of ecosystem fire probability as constrained by precipitation and temperature.

Science.gov (United States)

Guyette, Richard; Stambaugh, Michael C; Dey, Daniel; Muzika, Rose Marie

2017-01-01

The effects of climate on wildland fire confronts society across a range of different ecosystems. Water and temperature affect the combustion dynamics, irrespective of whether those are associated with carbon fueled motors or ecosystems, but through different chemical, physical, and biological processes. We use an ecosystem combustion equation developed with the physical chemistry of atmospheric variables to estimate and simulate fire probability and mean fire interval (MFI). The calibration of ecosystem fire probability with basic combustion chemistry and physics offers a quantitative method to address wildland fire in addition to the well-studied forcing factors such as topography, ignition, and vegetation. We develop a graphic analysis tool for estimating climate forced fire probability with temperature and precipitation based on an empirical assessment of combustion theory and fire prediction in ecosystems. Climate-affected fire probability for any period, past or future, is estimated with given temperature and precipitation. A graphic analyses of wildland fire dynamics driven by climate supports a dialectic in hydrologic processes that affect ecosystem combustion: 1) the water needed by plants to produce carbon bonds (fuel) and 2) the inhibition of successful reactant collisions by water molecules (humidity and fuel moisture). These two postulates enable a classification scheme for ecosystems into three or more climate categories using their position relative to change points defined by precipitation in combustion dynamics equations. Three classifications of combustion dynamics in ecosystems fire probability include: 1) precipitation insensitive, 2) precipitation unstable, and 3) precipitation sensitive. All three classifications interact in different ways with variable levels of temperature.

The theory, direction, and magnitude of ecosystem fire probability as constrained by precipitation and temperature.

Directory of Open Access Journals (Sweden)

Richard Guyette

Full Text Available The effects of climate on wildland fire confronts society across a range of different ecosystems. Water and temperature affect the combustion dynamics, irrespective of whether those are associated with carbon fueled motors or ecosystems, but through different chemical, physical, and biological processes. We use an ecosystem combustion equation developed with the physical chemistry of atmospheric variables to estimate and simulate fire probability and mean fire interval (MFI. The calibration of ecosystem fire probability with basic combustion chemistry and physics offers a quantitative method to address wildland fire in addition to the well-studied forcing factors such as topography, ignition, and vegetation. We develop a graphic analysis tool for estimating climate forced fire probability with temperature and precipitation based on an empirical assessment of combustion theory and fire prediction in ecosystems. Climate-affected fire probability for any period, past or future, is estimated with given temperature and precipitation. A graphic analyses of wildland fire dynamics driven by climate supports a dialectic in hydrologic processes that affect ecosystem combustion: 1 the water needed by plants to produce carbon bonds (fuel and 2 the inhibition of successful reactant collisions by water molecules (humidity and fuel moisture. These two postulates enable a classification scheme for ecosystems into three or more climate categories using their position relative to change points defined by precipitation in combustion dynamics equations. Three classifications of combustion dynamics in ecosystems fire probability include: 1 precipitation insensitive, 2 precipitation unstable, and 3 precipitation sensitive. All three classifications interact in different ways with variable levels of temperature.

A brief introduction to probability.

Science.gov (United States)

Di Paola, Gioacchino; Bertani, Alessandro; De Monte, Lavinia; Tuzzolino, Fabio

2018-02-01

The theory of probability has been debated for centuries: back in 1600, French mathematics used the rules of probability to place and win bets. Subsequently, the knowledge of probability has significantly evolved and is now an essential tool for statistics. In this paper, the basic theoretical principles of probability will be reviewed, with the aim of facilitating the comprehension of statistical inference. After a brief general introduction on probability, we will review the concept of the "probability distribution" that is a function providing the probabilities of occurrence of different possible outcomes of a categorical or continuous variable. Specific attention will be focused on normal distribution that is the most relevant distribution applied to statistical analysis.

Subjective socioeconomic status causes aggression: A test of the theory of social deprivation.

Science.gov (United States)

Greitemeyer, Tobias; Sagioglou, Christina

2016-08-01

Seven studies (overall N = 3690) addressed the relation between people's subjective socioeconomic status (SES) and their aggression levels. Based on relative deprivation theory, we proposed that people low in subjective SES would feel at a disadvantage, which in turn would elicit aggressive responses. In 3 correlational studies, subjective SES was negatively related to trait aggression. Importantly, this relation held when controlling for measures that are related to 1 or both subjective SES and trait aggression, such as the dark tetrad and the Big Five. Four experimental studies then demonstrated that participants in a low status condition were more aggressive than were participants in a high status condition. Compared with a medium-SES condition, participants of low subjective SES were more aggressive rather than participants of high subjective SES being less aggressive. Moreover, low SES increased aggressive behavior toward targets that were the source for participants' experience of disadvantage but also toward neutral targets. Sequential mediation analyses suggest that the experience of disadvantage underlies the effect of subjective SES on aggressive affect, whereas aggressive affect was the proximal determinant of aggressive behavior. Taken together, the present research found comprehensive support for key predictions derived from the theory of relative deprivation of how the perception of low SES is related to the person's judgments, emotional reactions, and actions. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Large deviations and idempotent probability

CERN Document Server

Puhalskii, Anatolii

2001-01-01

In the view of many probabilists, author Anatolii Puhalskii''s research results stand among the most significant achievements in the modern theory of large deviations. In fact, his work marked a turning point in the depth of our understanding of the connections between the large deviation principle (LDP) and well-known methods for establishing weak convergence results.Large Deviations and Idempotent Probability expounds upon the recent methodology of building large deviation theory along the lines of weak convergence theory. The author develops an idempotent (or maxitive) probability theory, introduces idempotent analogues of martingales (maxingales), Wiener and Poisson processes, and Ito differential equations, and studies their properties. The large deviation principle for stochastic processes is formulated as a certain type of convergence of stochastic processes to idempotent processes. The author calls this large deviation convergence.The approach to establishing large deviation convergence uses novel com...

On a paradox of probability theory

International Nuclear Information System (INIS)

Stuart, C.I.J.M.

1989-01-01

Costa de Beauregard's proposal concerning physical retrocausality has been shown to fail on two crucial points. However, it is argued that his proposal still merits serious attention. The argument arises from showing that his proposal reveals a paradox involving relations between conditional probabilities, statistical correlations and reciprocal causalities of the type exhibited by cooperative dynamics in physical systems. 4 refs. (Author)

Prospect balancing theory: Bounded rationality of drivers' speed choice.

Science.gov (United States)

Schmidt-Daffy, Martin

2014-02-01

This paper introduces a new approach to model the psychological determinants of drivers' speed choice: prospect-balancing theory. The theory transfers psychological insight into the bounded rationality of human decision-making to the field of driving behaviour. Speed choice is conceptualized as a trade-off between two options for action: the option to drive slower and the option to drive faster. Each option is weighted according to a subjective value and a subjectively weighted probability attributed to the achievement of the associated action goal; e.g. to avoid an accident by driving more slowly. The theory proposes that the subjective values and weightings of probability differ systematically from the objective conditions and thereby usually favour a cautious speed choice. A driving simulation study with 24 male participants supports this assumption. In a conflict between a monetary gain in case of fast arrival and a monetary loss in case of a collision with a deer, participants chose a velocity lower than that which would maximize their pay-out. Participants' subjective certainty of arriving in time and of avoiding a deer collision assessed at different driving speeds diverged from the respective objective probabilities in accordance with the observed bias in choice of speed. Results suggest that the bounded rationality of drivers' speed choice might be used to support attempts to improve road safety. Thus, understanding the motivational and perceptual determinants of this intuitive mode of decision-making might be a worthwhile focus of future research. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of event tree with imprecise inputs by fuzzy set theory

International Nuclear Information System (INIS)

Ahn, Kwang Il; Chun, Moon Hyun

1990-01-01

Fuzzy set theory approach is proposed as a method to analyze event trees with imprecise or linguistic input variables such as 'likely' or 'improbable' instead of the numerical probability. In this paper, it is shown how the fuzzy set theory can be applied to the event tree analysis. The result of this study shows that the fuzzy set theory approach can be applied as an acceptable and effective tool for analysis of the event tree with fuzzy type of inputs. Comparisons of the fuzzy theory approach with the probabilistic approach of computing probabilities of final states of the event tree through subjective weighting factors and LHS technique show that the two approaches have common factors and give reasonable results

Gas Hydrate Formation Probability Distributions: The Effect of Shear and Comparisons with Nucleation Theory.

Science.gov (United States)

May, Eric F; Lim, Vincent W; Metaxas, Peter J; Du, Jianwei; Stanwix, Paul L; Rowland, Darren; Johns, Michael L; Haandrikman, Gert; Crosby, Daniel; Aman, Zachary M

2018-03-13

Gas hydrate formation is a stochastic phenomenon of considerable significance for any risk-based approach to flow assurance in the oil and gas industry. In principle, well-established results from nucleation theory offer the prospect of predictive models for hydrate formation probability in industrial production systems. In practice, however, heuristics are relied on when estimating formation risk for a given flowline subcooling or when quantifying kinetic hydrate inhibitor (KHI) performance. Here, we present statistically significant measurements of formation probability distributions for natural gas hydrate systems under shear, which are quantitatively compared with theoretical predictions. Distributions with over 100 points were generated using low-mass, Peltier-cooled pressure cells, cycled in temperature between 40 and -5 °C at up to 2 K·min -1 and analyzed with robust algorithms that automatically identify hydrate formation and initial growth rates from dynamic pressure data. The application of shear had a significant influence on the measured distributions: at 700 rpm mass-transfer limitations were minimal, as demonstrated by the kinetic growth rates observed. The formation probability distributions measured at this shear rate had mean subcoolings consistent with theoretical predictions and steel-hydrate-water contact angles of 14-26°. However, the experimental distributions were substantially wider than predicted, suggesting that phenomena acting on macroscopic length scales are responsible for much of the observed stochastic formation. Performance tests of a KHI provided new insights into how such chemicals can reduce the risk of hydrate blockage in flowlines. Our data demonstrate that the KHI not only reduces the probability of formation (by both shifting and sharpening the distribution) but also reduces hydrate growth rates by a factor of 2.

Foundations of quantization for probability distributions

CERN Document Server

Graf, Siegfried

2000-01-01

Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first mathematically rigorous account of the fundamental theory underlying these applications. The emphasis is on the asymptotics of quantization errors for absolutely continuous and special classes of singular probabilities (surface measures, self-similar measures) presenting some new results for the first time. Written for researchers and graduate students in probability theory the monograph is of potential interest to all people working in the disciplines mentioned above.

Analytic methods in applied probability in memory of Fridrikh Karpelevich

CERN Document Server

Suhov, Yu M

2002-01-01

This volume is dedicated to F. I. Karpelevich, an outstanding Russian mathematician who made important contributions to applied probability theory. The book contains original papers focusing on several areas of applied probability and its uses in modern industrial processes, telecommunications, computing, mathematical economics, and finance. It opens with a review of Karpelevich's contributions to applied probability theory and includes a bibliography of his works. Other articles discuss queueing network theory, in particular, in heavy traffic approximation (fluid models). The book is suitable

Two-slit experiment: quantum and classical probabilities

International Nuclear Information System (INIS)

Khrennikov, Andrei

2015-01-01

Inter-relation between quantum and classical probability models is one of the most fundamental problems of quantum foundations. Nowadays this problem also plays an important role in quantum technologies, in quantum cryptography and the theory of quantum random generators. In this letter, we compare the viewpoint of Richard Feynman that the behavior of quantum particles cannot be described by classical probability theory with the viewpoint that quantum–classical inter-relation is more complicated (cf, in particular, with the tomographic model of quantum mechanics developed in detail by Vladimir Man'ko). As a basic example, we consider the two-slit experiment, which played a crucial role in quantum foundational debates at the beginning of quantum mechanics (QM). In particular, its analysis led Niels Bohr to the formulation of the principle of complementarity. First, we demonstrate that in complete accordance with Feynman's viewpoint, the probabilities for the two-slit experiment have the non-Kolmogorovian structure, since they violate one of basic laws of classical probability theory, the law of total probability (the heart of the Bayesian analysis). However, then we show that these probabilities can be embedded in a natural way into the classical (Kolmogorov, 1933) probability model. To do this, one has to take into account the randomness of selection of different experimental contexts, the joint consideration of which led Feynman to a conclusion about the non-classicality of quantum probability. We compare this embedding of non-Kolmogorovian quantum probabilities into the Kolmogorov model with well-known embeddings of non-Euclidean geometries into Euclidean space (e.g., the Poincaré disk model for the Lobachvesky plane). (paper)

Prediction and probability in sciences

International Nuclear Information System (INIS)

Klein, E.; Sacquin, Y.

1998-01-01

This book reports the 7 presentations made at the third meeting 'physics and fundamental questions' whose theme was probability and prediction. The concept of probability that was invented to apprehend random phenomena has become an important branch of mathematics and its application range spreads from radioactivity to species evolution via cosmology or the management of very weak risks. The notion of probability is the basis of quantum mechanics and then is bound to the very nature of matter. The 7 topics are: - radioactivity and probability, - statistical and quantum fluctuations, - quantum mechanics as a generalized probability theory, - probability and the irrational efficiency of mathematics, - can we foresee the future of the universe?, - chance, eventuality and necessity in biology, - how to manage weak risks? (A.C.)

Probability with applications in engineering, science, and technology

CERN Document Server

Carlton, Matthew A

2017-01-01

This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a year-long course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A one-term course would cover material in the core chapters (1-4), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stoch...

Selected papers on probability and statistics

CERN Document Server

2009-01-01

This volume contains translations of papers that originally appeared in the Japanese journal Sūgaku. The papers range over a variety of topics in probability theory, statistics, and applications. This volume is suitable for graduate students and research mathematicians interested in probability and statistics.

An Alternative Method to Compute the Bit Error Probability of Modulation Schemes Subject to Nakagami- Fading

Directory of Open Access Journals (Sweden)

Madeiro Francisco

2010-01-01

Full Text Available Abstract This paper presents an alternative method for determining exact expressions for the bit error probability (BEP of modulation schemes subject to Nakagami- fading. In this method, the Nakagami- fading channel is seen as an additive noise channel whose noise is modeled as the ratio between Gaussian and Nakagami- random variables. The method consists of using the cumulative density function of the resulting noise to obtain closed-form expressions for the BEP of modulation schemes subject to Nakagami- fading. In particular, the proposed method is used to obtain closed-form expressions for the BEP of -ary quadrature amplitude modulation ( -QAM, -ary pulse amplitude modulation ( -PAM, and rectangular quadrature amplitude modulation ( -QAM under Nakagami- fading. The main contribution of this paper is to show that this alternative method can be used to reduce the computational complexity for detecting signals in the presence of fading.

Probability for statisticians

CERN Document Server

Shorack, Galen R

2017-01-01

This 2nd edition textbook offers a rigorous introduction to measure theoretic probability with particular attention to topics of interest to mathematical statisticians—a textbook for courses in probability for students in mathematical statistics. It is recommended to anyone interested in the probability underlying modern statistics, providing a solid grounding in the probabilistic tools and techniques necessary to do theoretical research in statistics. For the teaching of probability theory to post graduate statistics students, this is one of the most attractive books available. Of particular interest is a presentation of the major central limit theorems via Stein's method either prior to or alternative to a characteristic function presentation. Additionally, there is considerable emphasis placed on the quantile function as well as the distribution function. The bootstrap and trimming are both presented. Martingale coverage includes coverage of censored data martingales. The text includes measure theoretic...

Image and Morphology in Modern Theory of Architecture

Science.gov (United States)

Yankovskaya, Y. S.; Merenkov, A. V.

2017-11-01

This paper is devoted to some important and fundamental problems of the modern Russian architectural theory. These problems are: methodological and technological retardation; substitution of the modern professional architectural theoretical knowledge by the humanitarian concepts; preference of the traditional historical or historical-theoretical research. One of the most probable ways is the formation of useful modern subject (and multi-subject)-oriented concepts in architecture. To get over the criticism and distrust of the architectural theory is possible through the recognition of an important role of the subject (architect, consumer, contractor, ruler, etc.) and direction of the practical tasks of the forming human environment in the today’s rapidly changing world and post-industrial society. In this article we consider the evolution of two basic concepts for the theory of architecture such as the image and morphology.

Improving subject recruitment, retention, and participation in research through Peplau's theory of interpersonal relations.

Science.gov (United States)

Penckofer, Sue; Byrn, Mary; Mumby, Patricia; Ferrans, Carol Estwing

2011-04-01

Recruitment and retention of persons participating in research is one of the most significant challenges faced by investigators. Although incentives are often used to improve recruitment and retention, evidence suggests that the relationship of the patient to study personnel may be the single, most important factor in subject accrual and continued participation. Peplau's theory of interpersonal relations provides a framework to study the nurse-patient relationship during the research process. In this paper the authors provide a brief summary of research strategies that have been used for the recruitment and retention of subjects and an overview of Peplau's theory of interpersonal relations including its use in research studies. In addition, a discussion of how this theory was used for the successful recruitment and retention of women with type 2 diabetes who participated in a clinical trial using a nurse-delivered psychoeducational intervention for depression is addressed.

Classical probabilities for Majorana and Weyl spinors

International Nuclear Information System (INIS)

Wetterich, C.

2011-01-01

Highlights: → Map of classical statistical Ising model to fermionic quantum field theory. → Lattice-regularized real Grassmann functional integral for single Weyl spinor. → Emerging complex structure characteristic for quantum physics. → A classical statistical ensemble describes a quantum theory. - Abstract: We construct a map between the quantum field theory of free Weyl or Majorana fermions and the probability distribution of a classical statistical ensemble for Ising spins or discrete bits. More precisely, a Grassmann functional integral based on a real Grassmann algebra specifies the time evolution of the real wave function q τ (t) for the Ising states τ. The time dependent probability distribution of a generalized Ising model obtains as p τ (t)=q τ 2 (t). The functional integral employs a lattice regularization for single Weyl or Majorana spinors. We further introduce the complex structure characteristic for quantum mechanics. Probability distributions of the Ising model which correspond to one or many propagating fermions are discussed explicitly. Expectation values of observables can be computed equivalently in the classical statistical Ising model or in the quantum field theory for fermions.

Daniel Courgeau: Probability and social science: methodological relationships between the two approaches [Review of: . Probability and social science: methodological relationships between the two approaches

NARCIS (Netherlands)

Willekens, F.J.C.

2013-01-01

Throughout history, humans engaged in games in which randomness plays a role. In the 17th century, scientists started to approach chance scientifically and to develop a theory of probability. Courgeau describes how the relationship between probability theory and social sciences emerged and evolved

Posterior Probability Matching and Human Perceptual Decision Making.

Directory of Open Access Journals (Sweden)

Richard F Murray

2015-06-01

Full Text Available Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models' performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods

Probability in reasoning: a developmental test on conditionals.

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Barrouillet, Pierre; Gauffroy, Caroline

2015-04-01

Probabilistic theories have been claimed to constitute a new paradigm for the psychology of reasoning. A key assumption of these theories is captured by what they call the Equation, the hypothesis that the meaning of the conditional is probabilistic in nature and that the probability of If p then q is the conditional probability, in such a way that P(if p then q)=P(q|p). Using the probabilistic truth-table task in which participants are required to evaluate the probability of If p then q sentences, the present study explored the pervasiveness of the Equation through ages (from early adolescence to adulthood), types of conditionals (basic, causal, and inducements) and contents. The results reveal that the Equation is a late developmental achievement only endorsed by a narrow majority of educated adults for certain types of conditionals depending on the content they involve. Age-related changes in evaluating the probability of all the conditionals studied closely mirror the development of truth-value judgements observed in previous studies with traditional truth-table tasks. We argue that our modified mental model theory can account for this development, and hence for the findings related with the probability task, which do not consequently support the probabilistic approach of human reasoning over alternative theories. Copyright © 2014 Elsevier B.V. All rights reserved.

Probabilities in physics

CERN Document Server

Hartmann, Stephan

2011-01-01

Many results of modern physics--those of quantum mechanics, for instance--come in a probabilistic guise. But what do probabilistic statements in physics mean? Are probabilities matters of objective fact and part of the furniture of the world, as objectivists think? Or do they only express ignorance or belief, as Bayesians suggest? And how are probabilistic hypotheses justified and supported by empirical evidence? Finally, what does the probabilistic nature of physics imply for our understanding of the world? This volume is the first to provide a philosophical appraisal of probabilities in all of physics. Its main aim is to make sense of probabilistic statements as they occur in the various physical theories and models and to provide a plausible epistemology and metaphysics of probabilities. The essays collected here consider statistical physics, probabilistic modelling, and quantum mechanics, and critically assess the merits and disadvantages of objectivist and subjectivist views of probabilities in these fie...

Introduction to probability with Mathematica

CERN Document Server

Hastings, Kevin J

2009-01-01

Discrete ProbabilityThe Cast of Characters Properties of Probability Simulation Random SamplingConditional ProbabilityIndependenceDiscrete DistributionsDiscrete Random Variables, Distributions, and ExpectationsBernoulli and Binomial Random VariablesGeometric and Negative Binomial Random Variables Poisson DistributionJoint, Marginal, and Conditional Distributions More on ExpectationContinuous ProbabilityFrom the Finite to the (Very) Infinite Continuous Random Variables and DistributionsContinuous ExpectationContinuous DistributionsThe Normal Distribution Bivariate Normal DistributionNew Random Variables from OldOrder Statistics Gamma DistributionsChi-Square, Student's t, and F-DistributionsTransformations of Normal Random VariablesAsymptotic TheoryStrong and Weak Laws of Large Numbers Central Limit TheoremStochastic Processes and ApplicationsMarkov ChainsPoisson Processes QueuesBrownian MotionFinancial MathematicsAppendixIntroduction to Mathematica Glossary of Mathematica Commands for Probability Short Answers...

Some open problems in noncommutative probability

International Nuclear Information System (INIS)

Kruszynski, P.

1981-01-01

A generalization of probability measures to non-Boolean structures is discussed. The starting point of the theory is the Gleason theorem about the form of measures on closed subspaces of a Hilbert space. The problems are formulated in terms of probability on lattices of projections in arbitrary von Neumann algebras. (Auth.)

Quantum probability and quantum decision-making.

Science.gov (United States)

Yukalov, V I; Sornette, D

2016-01-13

A rigorous general definition of quantum probability is given, which is valid not only for elementary events but also for composite events, for operationally testable measurements as well as for inconclusive measurements, and also for non-commuting observables in addition to commutative observables. Our proposed definition of quantum probability makes it possible to describe quantum measurements and quantum decision-making on the same common mathematical footing. Conditions are formulated for the case when quantum decision theory reduces to its classical counterpart and for the situation where the use of quantum decision theory is necessary. © 2015 The Author(s).

Probability with applications and R

CERN Document Server

Dobrow, Robert P

2013-01-01

An introduction to probability at the undergraduate level Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability. With real-life examples and thoughtful exercises from fields as diverse as biology, computer science, cryptology, ecology, public health, and sports, the book is accessible for a variety of readers. The book's emphasis on simulation through the use of the popular R software language c

Quantum decision theory as quantum theory of measurement

International Nuclear Information System (INIS)

Yukalov, V.I.; Sornette, D.

2008-01-01

We present a general theory of quantum information processing devices, that can be applied to human decision makers, to atomic multimode registers, or to molecular high-spin registers. Our quantum decision theory is a generalization of the quantum theory of measurement, endowed with an action ring, a prospect lattice and a probability operator measure. The algebra of probability operators plays the role of the algebra of local observables. Because of the composite nature of prospects and of the entangling properties of the probability operators, quantum interference terms appear, which make actions noncommutative and the prospect probabilities nonadditive. The theory provides the basis for explaining a variety of paradoxes typical of the application of classical utility theory to real human decision making. The principal advantage of our approach is that it is formulated as a self-consistent mathematical theory, which allows us to explain not just one effect but actually all known paradoxes in human decision making. Being general, the approach can serve as a tool for characterizing quantum information processing by means of atomic, molecular, and condensed-matter systems

Epistemology and Probability

CERN Document Server

Plotnitsky, Arkady

2010-01-01

Offers an exploration of the relationships between epistemology and probability in the work of Niels Bohr, Werner Heisenberg, and Erwin Schrodinger; in quantum mechanics; and in modern physics. This book considers the implications of these relationships and of quantum theory for our understanding of the nature of thinking and knowledge in general

A work-family conflict/subjective well-being process model: a test of competing theories of longitudinal effects.

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Matthews, Russell A; Wayne, Julie Holliday; Ford, Michael T

2014-11-01

In the present study, we examine competing predictions of stress reaction models and adaptation theories regarding the longitudinal relationship between work-family conflict and subjective well-being. Based on data from 432 participants over 3 time points with 2 lags of varying lengths (i.e., 1 month, 6 months), our findings suggest that in the short term, consistent with prior theory and research, work-family conflict is associated with poorer subjective well-being. Counter to traditional work-family predictions but consistent with adaptation theories, after accounting for concurrent levels of work-family conflict as well as past levels of subjective well-being, past exposure to work-family conflict was associated with higher levels of subjective well-being over time. Moreover, evidence was found for reverse causation in that greater subjective well-being at 1 point in time was associated with reduced work-family conflict at a subsequent point in time. Finally, the pattern of results did not vary as a function of using different temporal lags. We discuss the theoretical, research, and practical implications of our findings. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Probability Measures on Groups IX

CERN Document Server

1989-01-01

The latest in this series of Oberwolfach conferences focussed on the interplay between structural probability theory and various other areas of pure and applied mathematics such as Tauberian theory, infinite-dimensional rotation groups, central limit theorems, harmonizable processes, and spherical data. Thus it was attended by mathematicians whose research interests range from number theory to quantum physics in conjunction with structural properties of probabilistic phenomena. This volume contains 5 survey articles submitted on special invitation and 25 original research papers.

Quantum probabilities of composite events in quantum measurements with multimode states

International Nuclear Information System (INIS)

Yukalov, V I; Sornette, D

2013-01-01

The problem of defining quantum probabilities of composite events is considered. This problem is of great importance for the theory of quantum measurements and for quantum decision theory, which is a part of measurement theory. We show that the Lüders probability of consecutive measurements is a transition probability between two quantum states and that this probability cannot be treated as a quantum extension of the classical conditional probability. The Wigner distribution is shown to be a weighted transition probability that cannot be accepted as a quantum extension of the classical joint probability. We suggest the definition of quantum joint probabilities by introducing composite events in multichannel measurements. The notion of measurements under uncertainty is defined. We demonstrate that the necessary condition for mode interference is the entanglement of the composite prospect together with the entanglement of the composite statistical state. As an illustration, we consider an example of a quantum game. Special attention is paid to the application of the approach to systems with multimode states, such as atoms, molecules, quantum dots, or trapped Bose-condensed atoms with several coherent modes. (paper)

Predicting non-square 2D dice probabilities

Science.gov (United States)

Pender, G. A. T.; Uhrin, M.

2014-07-01

The prediction of the final state probabilities of a general cuboid randomly thrown onto a surface is a problem that naturally arises in the minds of men and women familiar with regular cubic dice and the basic concepts of probability. Indeed, it was considered by Newton in 1664 (Newton 1967 The Mathematical Papers of Issac Newton vol I (Cambridge: Cambridge University Press) pp 60-1). In this paper we make progress on the 2D problem (which can be realized in 3D by considering a long cuboid, or alternatively a rectangular cross-sectioned dreidel). For the two-dimensional case we suggest that the ratio of the probabilities of landing on each of the two sides is given by \\frac{\\sqrt{{{k}^{2}}+{{l}^{2}}}-k}{\\sqrt{{{k}^{2}}+{{l}^{2}}}-l}\\frac{arctan \\frac{l}{k}}{arctan \\frac{k}{l}} where k and l are the lengths of the two sides. We test this theory both experimentally and computationally, and find good agreement between our theory, experimental and computational results. Our theory is known, from its derivation, to be an approximation for particularly bouncy or ‘grippy’ surfaces where the die rolls through many revolutions before settling. On real surfaces we would expect (and we observe) that the true probability ratio for a 2D die is a somewhat closer to unity than predicted by our theory. This problem may also have wider relevance in the testing of physics engines.

EARLY HISTORY OF GEOMETRIC PROBABILITY AND STEREOLOGY

Directory of Open Access Journals (Sweden)

Magdalena Hykšová

2012-03-01

Full Text Available The paper provides an account of the history of geometric probability and stereology from the time of Newton to the early 20th century. It depicts the development of two parallel ways: on one hand, the theory of geometric probability was formed with minor attention paid to other applications than those concerning spatial chance games. On the other hand, practical rules of the estimation of area or volume fraction and other characteristics, easily deducible from geometric probability theory, were proposed without the knowledge of this branch. A special attention is paid to the paper of J.-É. Barbier published in 1860, which contained the fundamental stereological formulas, but remained almost unnoticed both by mathematicians and practicians.

Applied probability and stochastic processes

CERN Document Server

Sumita, Ushio

1999-01-01

Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...

The Use of Probability Theory as a Basis for Planning and Controlling Overhead Costs in Education and Industry. Final Report.

Science.gov (United States)

Vinson, R. B.

In this report, the author suggests changes in the treatment of overhead costs by hypothesizing that "the effectiveness of standard costing in planning and controlling overhead costs can be increased through the use of probability theory and associated statistical techniques." To test the hypothesis, the author (1) presents an overview of the…

Using Playing Cards to Differentiate Probability Interpretations

Science.gov (United States)

López Puga, Jorge

2014-01-01

The aprioristic (classical, naïve and symmetric) and frequentist interpretations of probability are commonly known. Bayesian or subjective interpretation of probability is receiving increasing attention. This paper describes an activity to help students differentiate between the three types of probability interpretations.

Probability an introduction with statistical applications

CERN Document Server

Kinney, John J

2014-01-01

Praise for the First Edition""This is a well-written and impressively presented introduction to probability and statistics. The text throughout is highly readable, and the author makes liberal use of graphs and diagrams to clarify the theory.""  - The StatisticianThoroughly updated, Probability: An Introduction with Statistical Applications, Second Edition features a comprehensive exploration of statistical data analysis as an application of probability. The new edition provides an introduction to statistics with accessible coverage of reliability, acceptance sampling, confidence intervals, h

Introduction to probability and statistics for science, engineering, and finance

CERN Document Server

Rosenkrantz, Walter A

2008-01-01

Data Analysis Orientation The Role and Scope of Statistics in Science and Engineering Types of Data: Examples from Engineering, Public Health, and Finance The Frequency Distribution of a Variable Defined on a Population Quantiles of a Distribution Measures of Location (Central Value) and Variability Covariance, Correlation, and Regression: Computing a Stock's Beta Mathematical Details and Derivations Large Data Sets Probability Theory Orientation Sample Space, Events, Axioms of Probability Theory Mathematical Models of Random Sampling Conditional Probability and Baye

Applied probability models with optimization applications

CERN Document Server

Ross, Sheldon M

1992-01-01

Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. ""Excellent introduction."" - Journal of the American Statistical Association. Bibliography. 1970 edition.

Probability inequalities for decomposition integrals

Czech Academy of Sciences Publication Activity Database

Agahi, H.; Mesiar, Radko

2017-01-01

Roč. 315, č. 1 (2017), s. 240-248 ISSN 0377-0427 Institutional support: RVO:67985556 Keywords : Decomposition integral * Superdecomposition integral * Probability inequalities Subject RIV: BA - General Mathematics OBOR OECD: Statistics and probability Impact factor: 1.357, year: 2016 http://library.utia.cas.cz/separaty/2017/E/mesiar-0470959.pdf

The mathematics of various entertaining subjects

CERN Document Server

Rosenhouse, Jason

Volume 1 : The history of mathematics is filled with major breakthroughs resulting from solutions to recreational problems. Problems of interest to gamblers led to the modern theory of probability, for example, and surreal numbers were inspired by the game of Go. Yet even with such groundbreaking findings and a wealth of popular-level books exploring puzzles and brainteasers, research in recreational mathematics has often been neglected. The Mathematics of Various Entertaining Subjects brings together authors from a variety of specialties to present fascinating problems and solutions in recreational mathematics. Contributors to the book show how sophisticated mathematics can help construct mazes that look like famous people, how the analysis of crossword puzzles has much in common with understanding epidemics, and how the theory of electrical circuits is useful in understanding the classic Towers of Hanoi puzzle. The card game SET is related to the theory of error-correcting codes, and simple tic-tac-toe tak...

Joint probabilities and quantum cognition

International Nuclear Information System (INIS)

Acacio de Barros, J.

2012-01-01

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Joint probabilities and quantum cognition

Energy Technology Data Exchange (ETDEWEB)

Acacio de Barros, J. [Liberal Studies, 1600 Holloway Ave., San Francisco State University, San Francisco, CA 94132 (United States)

2012-12-18

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Decision making generalized by a cumulative probability weighting function

Science.gov (United States)

dos Santos, Lindomar Soares; Destefano, Natália; Martinez, Alexandre Souto

2018-01-01

Typical examples of intertemporal decision making involve situations in which individuals must choose between a smaller reward, but more immediate, and a larger one, delivered later. Analogously, probabilistic decision making involves choices between options whose consequences differ in relation to their probability of receiving. In Economics, the expected utility theory (EUT) and the discounted utility theory (DUT) are traditionally accepted normative models for describing, respectively, probabilistic and intertemporal decision making. A large number of experiments confirmed that the linearity assumed by the EUT does not explain some observed behaviors, as nonlinear preference, risk-seeking and loss aversion. That observation led to the development of new theoretical models, called non-expected utility theories (NEUT), which include a nonlinear transformation of the probability scale. An essential feature of the so-called preference function of these theories is that the probabilities are transformed by decision weights by means of a (cumulative) probability weighting function, w(p) . We obtain in this article a generalized function for the probabilistic discount process. This function has as particular cases mathematical forms already consecrated in the literature, including discount models that consider effects of psychophysical perception. We also propose a new generalized function for the functional form of w. The limiting cases of this function encompass some parametric forms already proposed in the literature. Far beyond a mere generalization, our function allows the interpretation of probabilistic decision making theories based on the assumption that individuals behave similarly in the face of probabilities and delays and is supported by phenomenological models.

Nuclear data uncertainties: I, Basic concepts of probability

Energy Technology Data Exchange (ETDEWEB)

Smith, D.L.

1988-12-01

Some basic concepts of probability theory are presented from a nuclear-data perspective, in order to provide a foundation for thorough understanding of the role of uncertainties in nuclear data research. Topics included in this report are: events, event spaces, calculus of events, randomness, random variables, random-variable distributions, intuitive and axiomatic probability, calculus of probability, conditional probability and independence, probability distributions, binomial and multinomial probability, Poisson and interval probability, normal probability, the relationships existing between these probability laws, and Bayes' theorem. This treatment emphasizes the practical application of basic mathematical concepts to nuclear data research, and it includes numerous simple examples. 34 refs.

Nuclear data uncertainties: I, Basic concepts of probability

International Nuclear Information System (INIS)

Smith, D.L.

1988-12-01

Some basic concepts of probability theory are presented from a nuclear-data perspective, in order to provide a foundation for thorough understanding of the role of uncertainties in nuclear data research. Topics included in this report are: events, event spaces, calculus of events, randomness, random variables, random-variable distributions, intuitive and axiomatic probability, calculus of probability, conditional probability and independence, probability distributions, binomial and multinomial probability, Poisson and interval probability, normal probability, the relationships existing between these probability laws, and Bayes' theorem. This treatment emphasizes the practical application of basic mathematical concepts to nuclear data research, and it includes numerous simple examples. 34 refs

Logic, probability, and human reasoning.

Science.gov (United States)

Johnson-Laird, P N; Khemlani, Sangeet S; Goodwin, Geoffrey P

2015-04-01

This review addresses the long-standing puzzle of how logic and probability fit together in human reasoning. Many cognitive scientists argue that conventional logic cannot underlie deductions, because it never requires valid conclusions to be withdrawn - not even if they are false; it treats conditional assertions implausibly; and it yields many vapid, although valid, conclusions. A new paradigm of probability logic allows conclusions to be withdrawn and treats conditionals more plausibly, although it does not address the problem of vapidity. The theory of mental models solves all of these problems. It explains how people reason about probabilities and postulates that the machinery for reasoning is itself probabilistic. Recent investigations accordingly suggest a way to integrate probability and deduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exact closed form expressions for outage probability of GSC receivers over Rayleigh fading channel subject to self-interference

KAUST Repository

Nam, Sungsik

2010-11-01

Previous work on performance analyses of generalized selection combining (GSC) RAKE receivers based on the signal to noise ratio focused on the development of methodologies to derive exact closed-form expressions for various performance measures. However, some open problems related to the performance evaluation of GSC RAKE receivers still remain to be solved such that an assessment of the impact of self-interference on the performance of GSC RAKE receivers. To have a full and exact understanding of the performance of GSC RAKE receivers, the outage probability of GSC RAKE receivers needs to be analyzed as closed-form expressions. The major difficulty in this problem is to derive some joint statistics of ordered exponential variates. With this motivation in mind, we capitalize in this paper on some new order statistics results to derive exact closed-form expressions for outage probability of GSC RAKE receivers subject to self-interference over independent and identically distributed Rayleigh fading channels. © 2010 IEEE.

The philosophical basis for the use of probabilities in safety assessments

International Nuclear Information System (INIS)

Abramson, L.R.

1988-01-01

The axiomatic theory of probability is analogous to the theory of moving objects based on relations such as Newton's second law, F = ma. Each theory purports to describe the behavior of physical objects, and each has been validated by countless observations and experiments. In this sense, the probability of coming up heads is just as intrinsic a property of a real coin as is its mass. In contrast to the established validity of the axiomatic approach, the major weakness of the subjectivistic (Bayesian) approach to probability is the questionable connection between its conclusions and the real world. (author)

Probability model for analyzing fire management alternatives: theory and structure

Science.gov (United States)

Frederick W. Bratten

1982-01-01

A theoretical probability model has been developed for analyzing program alternatives in fire management. It includes submodels or modules for predicting probabilities of fire behavior, fire occurrence, fire suppression, effects of fire on land resources, and financial effects of fire. Generalized "fire management situations" are used to represent actual fire...

Introducing Disjoint and Independent Events in Probability.

Science.gov (United States)

Kelly, I. W.; Zwiers, F. W.

Two central concepts in probability theory are those of independence and mutually exclusive events. This document is intended to provide suggestions to teachers that can be used to equip students with an intuitive, comprehensive understanding of these basic concepts in probability. The first section of the paper delineates mutually exclusive and…

Monte Carlo simulation of γ and fission transfer-induced probabilities using extended -matrix theory: Application to the 237U∗ system

Directory of Open Access Journals (Sweden)

Bouland Olivier

2017-01-01

Full Text Available This paper deals with simultaneous neutron-induced average partial cross sections and surrogate-like probability simulations over several excitation and de-excitation channels of the compound nucleus. Present calculations, based on one-dimensional fission barrier extended -matrix theory using Monte Carlo samplings of both first and second well resonance parameters, avoid the surrogate-reaction method historically taken for surrogate data analyses that proved to be very poor in terms of extrapolated neutron-induced capture cross sections. Present theoretical approach is portrayed and subsequent results can be compared for the first time with experimental γ-decay probabilities; thanks to brand new simultaneous 238U(3He,4Heγ and 238U(3He,4He f surrogate measurements. Future integration of our strategy in standard neutron cross section data evaluation remains tied to the developments made in terms of direct reaction population probability calculations.

The Influence of Subjective Life Expectancy on Retirement Transition and Planning: A Longitudinal Study

Science.gov (United States)

Griffin, Barbara; Hesketh, Beryl; Loh, Vanessa

2012-01-01

This study examines the construct of subjective life expectancy (SLE), or the estimation of one's probable age of death. Drawing on the tenets of socioemotional selectivity theory (Carstensen, Isaacowitz, & Charles, 1999), we propose that SLE provides individuals with their own unique mental model of remaining time that is likely to affect their…

The theory of quantum information

CERN Document Server

Watrous, John

2018-01-01

This largely self-contained book on the theory of quantum information focuses on precise mathematical formulations and proofs of fundamental facts that form the foundation of the subject. It is intended for graduate students and researchers in mathematics, computer science, and theoretical physics seeking to develop a thorough understanding of key results, proof techniques, and methodologies that are relevant to a wide range of research topics within the theory of quantum information and computation. The book is accessible to readers with an understanding of basic mathematics, including linear algebra, mathematical analysis, and probability theory. An introductory chapter summarizes these necessary mathematical prerequisites, and starting from this foundation, the book includes clear and complete proofs of all results it presents. Each subsequent chapter includes challenging exercises intended to help readers to develop their own skills for discovering proofs concerning the theory of quantum information.

An introduction to probability and stochastic processes

CERN Document Server

Melsa, James L

2013-01-01

Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.

Truth, possibility and probability new logical foundations of probability and statistical inference

CERN Document Server

Chuaqui, R

1991-01-01

Anyone involved in the philosophy of science is naturally drawn into the study of the foundations of probability. Different interpretations of probability, based on competing philosophical ideas, lead to different statistical techniques, and frequently to mutually contradictory consequences. This unique book presents a new interpretation of probability, rooted in the traditional interpretation that was current in the 17th and 18th centuries. Mathematical models are constructed based on this interpretation, and statistical inference and decision theory are applied, including some examples in artificial intelligence, solving the main foundational problems. Nonstandard analysis is extensively developed for the construction of the models and in some of the proofs. Many nonstandard theorems are proved, some of them new, in particular, a representation theorem that asserts that any stochastic process can be approximated by a process defined over a space with equiprobable outcomes.

Optimal Volume for Concert Halls Based on Ando’s Subjective Preference and Barron Revised Theories

Directory of Open Access Journals (Sweden)

Salvador Cerdá

2014-03-01

Full Text Available The Ando-Beranek’s model, a linear version of Ando’s subjective preference theory, obtained by the authors in a recent work, was combined with Barron revised theory. An optimal volume region for each reverberation time was obtained for classical music in symphony orchestra concert halls. The obtained relation was tested with good agreement with the top rated halls reported by Beranek and other halls with reported anomalies.

Prospect theory on the brain? Toward a cognitive neuroscience of decision under risk.

Science.gov (United States)

Trepel, Christopher; Fox, Craig R; Poldrack, Russell A

2005-04-01

Most decisions must be made without advance knowledge of their consequences. Economists and psychologists have devoted much attention to modeling decisions made under conditions of risk in which options can be characterized by a known probability distribution over possible outcomes. The descriptive shortcomings of classical economic models motivated the development of prospect theory (D. Kahneman, A. Tversky, Prospect theory: An analysis of decision under risk. Econometrica, 4 (1979) 263-291; A. Tversky, D. Kahneman, Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5 (4) (1992) 297-323) the most successful behavioral model of decision under risk. In the prospect theory, subjective value is modeled by a value function that is concave for gains, convex for losses, and steeper for losses than for gains; the impact of probabilities are characterized by a weighting function that overweights low probabilities and underweights moderate to high probabilities. We outline the possible neural bases of the components of prospect theory, surveying evidence from human imaging, lesion, and neuropharmacology studies as well as animal neurophysiology studies. These results provide preliminary suggestions concerning the neural bases of prospect theory that include a broad set of brain regions and neuromodulatory systems. These data suggest that focused studies of decision making in the context of quantitative models may provide substantial leverage towards a fuller understanding of the cognitive neuroscience of decision making.

Integrated data analysis of fusion diagnostics by means of the Bayesian probability theory

International Nuclear Information System (INIS)

Fischer, R.; Dinklage, A.

2004-01-01

Integrated data analysis (IDA) of fusion diagnostics is the combination of heterogeneous diagnostics to obtain validated physical results. Benefits from the integrated approach result from a systematic use of interdependencies; in that sense IDA optimizes the extraction of information from sets of different data. For that purpose IDA requires a systematic and formalized error analysis of all (statistical and systematic) uncertainties involved in each diagnostic. Bayesian probability theory allows for a systematic combination of all information entering the diagnostic model by considering all uncertainties of the measured data, the calibration measurements, and the physical model. Prior physics knowledge on model parameters can be included. Handling of systematic errors is provided. A central goal of the integration of redundant or complementary diagnostics is to provide information to resolve inconsistencies by exploiting interdependencies. A comparable analysis of sets of diagnostics (meta-diagnostics) is performed by combining statistical and systematical uncertainties with model parameters and model uncertainties. Diagnostics improvement and experimental optimization and design of meta-diagnostics will be discussed

p-adic probability interpretation of Bell's inequality

International Nuclear Information System (INIS)

Khrennikov, A.

1995-01-01

We study the violation of Bell's inequality using a p-adic generalization of the theory of probability. p-adic probability is introduced as a limit of relative frequencies but this limit exists with respect to a p-adic metric. In particular, negative probability distributions are well defined on the basis of the frequency definition. This new type of stochastics can be used to describe hidden-variables distributions of some quantum models. If the hidden variables have a p-adic probability distribution, Bell's inequality is not valid and it is not necessary to discuss the experimental violations of this inequality. ((orig.))

On the discretization of probability density functions and the ...

Indian Academy of Sciences (India)

important for most applications or theoretical problems of interest. In statistics ... In probability theory, statistics, statistical mechanics, communication theory, and other .... (1) by taking advantage of SMVT as a general mathematical approach.

Knot probability of polygons subjected to a force: a Monte Carlo study

International Nuclear Information System (INIS)

Rensburg, E J Janse van; Orlandini, E; Tesi, M C; Whittington, S G

2008-01-01

We use Monte Carlo methods to study the knot probability of lattice polygons on the cubic lattice in the presence of an external force f. The force is coupled to the span of the polygons along a lattice direction, say the z-direction. If the force is negative polygons are squeezed (the compressive regime), while positive forces tend to stretch the polygons along the z-direction (the tensile regime). For sufficiently large positive forces we verify that the Pincus scaling law in the force-extension curve holds. At a fixed number of edges n the knot probability is a decreasing function of the force. For a fixed force the knot probability approaches unity as 1 - exp(-α 0 (f)n + o(n)), where α 0 (f) is positive and a decreasing function of f. We also examine the average of the absolute value of the writhe and we verify the square root growth law (known for f = 0) for all values of f

Average bit error probability of binary coherent signaling over generalized fading channels subject to additive generalized gaussian noise

KAUST Repository

Soury, Hamza

2012-06-01

This letter considers the average bit error probability of binary coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closed form expression in terms of the Fox\\'s H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading and Nakagami-m fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters. © 2012 IEEE.

Counterexamples in probability

CERN Document Server

Stoyanov, Jordan M

2013-01-01

While most mathematical examples illustrate the truth of a statement, counterexamples demonstrate a statement's falsity. Enjoyable topics of study, counterexamples are valuable tools for teaching and learning. The definitive book on the subject in regards to probability, this third edition features the author's revisions and corrections plus a substantial new appendix.

Probability for Weather and Climate

Science.gov (United States)

Smith, L. A.

2013-12-01

Over the last 60 years, the availability of large-scale electronic computers has stimulated rapid and significant advances both in meteorology and in our understanding of the Earth System as a whole. The speed of these advances was due, in large part, to the sudden ability to explore nonlinear systems of equations. The computer allows the meteorologist to carry a physical argument to its conclusion; the time scales of weather phenomena then allow the refinement of physical theory, numerical approximation or both in light of new observations. Prior to this extension, as Charney noted, the practicing meteorologist could ignore the results of theory with good conscience. Today, neither the practicing meteorologist nor the practicing climatologist can do so, but to what extent, and in what contexts, should they place the insights of theory above quantitative simulation? And in what circumstances can one confidently estimate the probability of events in the world from model-based simulations? Despite solid advances of theory and insight made possible by the computer, the fidelity of our models of climate differs in kind from the fidelity of models of weather. While all prediction is extrapolation in time, weather resembles interpolation in state space, while climate change is fundamentally an extrapolation. The trichotomy of simulation, observation and theory which has proven essential in meteorology will remain incomplete in climate science. Operationally, the roles of probability, indeed the kinds of probability one has access too, are different in operational weather forecasting and climate services. Significant barriers to forming probability forecasts (which can be used rationally as probabilities) are identified. Monte Carlo ensembles can explore sensitivity, diversity, and (sometimes) the likely impact of measurement uncertainty and structural model error. The aims of different ensemble strategies, and fundamental differences in ensemble design to support of

Information-theoretic methods for estimating of complicated probability distributions

CERN Document Server

Zong, Zhi

2006-01-01

Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur

Theory of overdispersion in counting statistics caused by fluctuating probabilities

International Nuclear Information System (INIS)

Semkow, Thomas M.

1999-01-01

It is shown that the random Lexis fluctuations of probabilities such as probability of decay or detection cause the counting statistics to be overdispersed with respect to the classical binomial, Poisson, or Gaussian distributions. The generating and the distribution functions for the overdispersed counting statistics are derived. Applications to radioactive decay with detection and more complex experiments are given, as well as distinguishing between the source and background, in the presence of overdispersion. Monte-Carlo verifications are provided

Exploring non-signalling polytopes with negative probability

International Nuclear Information System (INIS)

Oas, G; Barros, J Acacio de; Carvalhaes, C

2014-01-01

Bipartite and tripartite EPR–Bell type systems are examined via joint quasi-probability distributions where probabilities are permitted to be negative. It is shown that such distributions exist only when the no-signalling condition is satisfied. A characteristic measure, the probability mass, is introduced and, via its minimization, limits the number of quasi-distributions describing a given marginal probability distribution. The minimized probability mass is shown to be an alternative way to characterize non-local systems. Non-signalling polytopes for two to eight settings in the bipartite scenario are examined and compared to prior work. Examining perfect cloning of non-local systems within the tripartite scenario suggests defining two categories of signalling. It is seen that many properties of non-local systems can be efficiently described by quasi-probability theory. (paper)

Fundamentals of applied probability and random processes

CERN Document Server

Ibe, Oliver

2005-01-01

This book is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book''s clear writing style and homework problems make it ideal for the classroom or for self-study.* Good and solid introduction to probability theory and stochastic processes * Logically organized; writing is presented in a clear manner * Choice of topics is comprehensive within the area of probability * Ample homework problems are organized into chapter sections

Probability, Statistics, and Stochastic Processes

CERN Document Server

Olofsson, Peter

2011-01-01

A mathematical and intuitive approach to probability, statistics, and stochastic processes This textbook provides a unique, balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. This text combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The text begins with three chapters that d

A Quantum Theoretical Explanation for Probability Judgment Errors

Science.gov (United States)

Busemeyer, Jerome R.; Pothos, Emmanuel M.; Franco, Riccardo; Trueblood, Jennifer S.

2011-01-01

A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and disjunction fallacies, averaging effects, unpacking effects, and order effects on inference. On the one hand, quantum theory is similar to other categorization and memory models of cognition in that it relies on vector…

Prospect theory: A parametric analysis of functional forms in Brazil

Directory of Open Access Journals (Sweden)

Robert Eugene Lobel

2017-10-01

Full Text Available This study aims to analyze risk preferences in Brazil based on prospect theory by estimating the risk aversion parameter of the expected utility theory (EUT for a select sample, in addition to the value and probability function parameter, assuming various functional forms, and a newly proposed value function, the modified log. This is the first such study in Brazil, and the parameter results are slightly different from studies in other countries, indicating that subjects are more risk averse and exhibit a smaller loss aversion. Probability distortion is the only common factor. As expected, the study finds that behavioral models are superior to EUT, and models based on prospect theory, the TK and Prelec weighting function, and the value power function show superior performance to others. Finally, the modified log function proposed in the study fits the data well, and can thus be used for future studies in Brazil.

Greek paideia and terms of probability

Directory of Open Access Journals (Sweden)

Fernando Leon Parada

2016-06-01

Full Text Available This paper addresses three aspects of the conceptual framework for a doctoral dissertation research in process in the field of Mathematics Education, in particular, in the subfield of teaching and learning basic concepts of Probability Theory at the College level. It intends to contrast, sustain and elucidate the central statement that the meanings of some of these basic terms used in Probability Theory were not formally defined by any specific theory but relate to primordial ideas developed in Western culture from Ancient Greek myths. The first aspect deals with the notion of uncertainty, with that Greek thinkers described several archaic gods and goddesses of Destiny, like Parcas and Moiras, often personified in the goddess Tyche—Fortuna for the Romans—, as regarded in Werner Jaeger’s “Paideia”. The second aspect treats the idea of hazard from two different approaches: the first approach deals with hazard, denoted by Plato with the already demythologized term ‘tyche’ from the viewpoint of innate knowledge, as Jaeger points out. The second approach deals with hazard from a perspective that could be called “phenomenological”, from which Aristotle attempted to articulate uncertainty with a discourse based on the hypothesis of causality. The term ‘causal’ was opposed both to ‘casual’ and to ‘spontaneous’ (as used in the expression “spontaneous generation”, attributing uncertainty to ignorance of the future, thus respecting causal flow. The third aspect treated in the paper refers to some definitions and etymologies of some other modern words that have become technical terms in current Probability Theory, confirming the above-mentioned main proposition of this paper.

Decision analysis with cumulative prospect theory.

Science.gov (United States)

Bayoumi, A M; Redelmeier, D A

2000-01-01

Individuals sometimes express preferences that do not follow expected utility theory. Cumulative prospect theory adjusts for some phenomena by using decision weights rather than probabilities when analyzing a decision tree. The authors examined how probability transformations from cumulative prospect theory might alter a decision analysis of a prophylactic therapy in AIDS, eliciting utilities from patients with HIV infection (n = 75) and calculating expected outcomes using an established Markov model. They next focused on transformations of three sets of probabilities: 1) the probabilities used in calculating standard-gamble utility scores; 2) the probabilities of being in discrete Markov states; 3) the probabilities of transitioning between Markov states. The same prophylaxis strategy yielded the highest quality-adjusted survival under all transformations. For the average patient, prophylaxis appeared relatively less advantageous when standard-gamble utilities were transformed. Prophylaxis appeared relatively more advantageous when state probabilities were transformed and relatively less advantageous when transition probabilities were transformed. Transforming standard-gamble and transition probabilities simultaneously decreased the gain from prophylaxis by almost half. Sensitivity analysis indicated that even near-linear probability weighting transformations could substantially alter quality-adjusted survival estimates. The magnitude of benefit estimated in a decision-analytic model can change significantly after using cumulative prospect theory. Incorporating cumulative prospect theory into decision analysis can provide a form of sensitivity analysis and may help describe when people deviate from expected utility theory.

Probability and statistics for computer science

CERN Document Server

Johnson, James L

2011-01-01

Comprehensive and thorough development of both probability and statistics for serious computer scientists; goal-oriented: ""to present the mathematical analysis underlying probability results"" Special emphases on simulation and discrete decision theory Mathematically-rich, but self-contained text, at a gentle pace Review of calculus and linear algebra in an appendix Mathematical interludes (in each chapter) which examine mathematical techniques in the context of probabilistic or statistical importance Numerous section exercises, summaries, historical notes, and Further Readings for reinforcem

Foundations of compositional model theory

Czech Academy of Sciences Publication Activity Database

Jiroušek, Radim

2011-01-01

Roč. 40, č. 6 (2011), s. 623-678 ISSN 0308-1079 R&D Projects: GA MŠk 1M0572; GA ČR GA201/09/1891; GA ČR GEICC/08/E010 Institutional research plan: CEZ:AV0Z10750506 Keywords : multidimensional probability distribution * conditional independence * graphical Markov model * composition of distributions Subject RIV: IN - Informatics, Computer Science Impact factor: 0.667, year: 2011 http://library.utia.cas.cz/separaty/2011/MTR/jirousek-foundations of compositional model theory.pdf

Probability estimation with machine learning methods for dichotomous and multicategory outcome: theory.

Science.gov (United States)

Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas

2014-07-01

Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Consistent probabilities in loop quantum cosmology

International Nuclear Information System (INIS)

Craig, David A; Singh, Parampreet

2013-01-01

A fundamental issue for any quantum cosmological theory is to specify how probabilities can be assigned to various quantum events or sequences of events such as the occurrence of singularities or bounces. In previous work, we have demonstrated how this issue can be successfully addressed within the consistent histories approach to quantum theory for Wheeler–DeWitt-quantized cosmological models. In this work, we generalize that analysis to the exactly solvable loop quantization of a spatially flat, homogeneous and isotropic cosmology sourced with a massless, minimally coupled scalar field known as sLQC. We provide an explicit, rigorous and complete decoherent-histories formulation for this model and compute the probabilities for the occurrence of a quantum bounce versus a singularity. Using the scalar field as an emergent internal time, we show for generic states that the probability for a singularity to occur in this model is zero, and that of a bounce is unity, complementing earlier studies of the expectation values of the volume and matter density in this theory. We also show from the consistent histories point of view that all states in this model, whether quantum or classical, achieve arbitrarily large volume in the limit of infinite ‘past’ or ‘future’ scalar ‘time’, in the sense that the wave function evaluated at any arbitrary fixed value of the volume vanishes in that limit. Finally, we briefly discuss certain misconceptions concerning the utility of the consistent histories approach in these models. (paper)

Random vibrations theory and practice

CERN Document Server

Wirsching, Paul H; Ortiz, Keith

1995-01-01

Random Vibrations: Theory and Practice covers the theory and analysis of mechanical and structural systems undergoing random oscillations due to any number of phenomena— from engine noise, turbulent flow, and acoustic noise to wind, ocean waves, earthquakes, and rough pavement. For systems operating in such environments, a random vibration analysis is essential to the safety and reliability of the system. By far the most comprehensive text available on random vibrations, Random Vibrations: Theory and Practice is designed for readers who are new to the subject as well as those who are familiar with the fundamentals and wish to study a particular topic or use the text as an authoritative reference. It is divided into three major sections: fundamental background, random vibration development and applications to design, and random signal analysis. Introductory chapters cover topics in probability, statistics, and random processes that prepare the reader for the development of the theory of random vibrations a...

Probability theory and statistical applications a profound treatise for self-study

CERN Document Server

Zörnig, Peter

2016-01-01

This accessible and easy-to-read book provides many examples to illustrate diverse topics in probability and statistics, from initial concepts up to advanced calculations. Special attention is devoted e.g. to independency of events, inequalities in probability and functions of random variables. The book is directed to students of mathematics, statistics, engineering, and other quantitative sciences.

Limiting values of large deviation probabilities of quadratic statistics

NARCIS (Netherlands)

Jeurnink, Gerardus A.M.; Kallenberg, W.C.M.

1990-01-01

Application of exact Bahadur efficiencies in testing theory or exact inaccuracy rates in estimation theory needs evaluation of large deviation probabilities. Because of the complexity of the expressions, frequently a local limit of the nonlocal measure is considered. Local limits of large deviation

Measurement Errors and Uncertainties Theory and Practice

CERN Document Server

Rabinovich, Semyon G

2006-01-01

Measurement Errors and Uncertainties addresses the most important problems that physicists and engineers encounter when estimating errors and uncertainty. Building from the fundamentals of measurement theory, the author develops the theory of accuracy of measurements and offers a wealth of practical recommendations and examples of applications. This new edition covers a wide range of subjects, including: - Basic concepts of metrology - Measuring instruments characterization, standardization and calibration -Estimation of errors and uncertainty of single and multiple measurements - Modern probability-based methods of estimating measurement uncertainty With this new edition, the author completes the development of the new theory of indirect measurements. This theory provides more accurate and efficient methods for processing indirect measurement data. It eliminates the need to calculate the correlation coefficient - a stumbling block in measurement data processing - and offers for the first time a way to obtain...

Fitness Probability Distribution of Bit-Flip Mutation.

Science.gov (United States)

Chicano, Francisco; Sutton, Andrew M; Whitley, L Darrell; Alba, Enrique

2015-01-01

Bit-flip mutation is a common mutation operator for evolutionary algorithms applied to optimize functions over binary strings. In this paper, we develop results from the theory of landscapes and Krawtchouk polynomials to exactly compute the probability distribution of fitness values of a binary string undergoing uniform bit-flip mutation. We prove that this probability distribution can be expressed as a polynomial in p, the probability of flipping each bit. We analyze these polynomials and provide closed-form expressions for an easy linear problem (Onemax), and an NP-hard problem, MAX-SAT. We also discuss a connection of the results with runtime analysis.

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

Science.gov (United States)

Ben-David, Avishai; Davidson, Charles E

2012-04-23

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

Dynamic analysis of isotropic nanoplates subjected to moving load using state-space method based on nonlocal second order plate theory

Energy Technology Data Exchange (ETDEWEB)

Nami, Mohammad Rahim [Shiraz University, Shiraz, Iran (Iran, Islamic Republic of); Janghorban, Maziar [Islamic Azad University, Marvdash (Iran, Islamic Republic of)

2015-06-15

In this work, dynamic analysis of rectangular nanoplates subjected to moving load is presented. In order to derive the governing equations of motion, second order plate theory is used. To capture the small scale effects, the nonlocal elasticity theory is adopted. It is assumed that the nanoplate is subjected to a moving concentrated load with the constant velocity V in the x direction. To solve the governing equations, state-space method is used to find the deflections of rectangular nanoplate under moving load. The results obtained here reveal that the nonlocality has significant effect on the deflection of rectangular nanoplate subjected to moving load.

Introduction to Probability, Part 1 - Basic Concepts. Student Text. Revised Edition.

Science.gov (United States)

Blakeslee, David W.; And Others

This book is designed to introduce the reader to some fundamental ideas about probability. The mathematical theory of probability plays an increasingly important role in science, government, industry, business, and economics. An understanding of the basic concepts of probability is essential for the study of statistical methods that are widely…

Upper Bounds for Ruin Probability with Stochastic Investment Return

Institute of Scientific and Technical Information of China (English)

ZHANG Lihong

2005-01-01

Risk models with stochastic investment return are widely held in practice, as well as in more challenging research fields. Risk theory is mainly concerned with ruin probability, and a tight bound for ruin probability is the best for practical use. This paper presents a discrete time risk model with stochastic investment return. Conditional expectation properties and martingale inequalities are used to obtain both exponential and non-exponential upper bounds for the ruin probability.

Theory of semigroups and applications

CERN Document Server

Sinha, Kalyan B

2017-01-01

The book presents major topics in semigroups, such as operator theory, partial differential equations, harmonic analysis, probability and statistics and classical and quantum mechanics, and applications. Along with a systematic development of the subject, the book emphasises on the explorations of the contact areas and interfaces, supported by the presentations of explicit computations, wherever feasible. Designed into seven chapters and three appendixes, the book targets to the graduate and senior undergraduate students of mathematics, as well as researchers in the respective areas. The book envisages the pre-requisites of a good understanding of real analysis with elements of the theory of measures and integration, and a first course in functional analysis and in the theory of operators. Chapters 4 through 6 contain advanced topics, which have many interesting applications such as the Feynman–Kac formula, the central limit theorem and the construction of Markov semigroups. Many examples have been given in...

Random phenomena fundamentals of probability and statistics for engineers

CERN Document Server

Ogunnaike, Babatunde A

2009-01-01

PreludeApproach PhilosophyFour Basic PrinciplesI FoundationsTwo Motivating ExamplesYield Improvement in a Chemical ProcessQuality Assurance in a Glass Sheet Manufacturing ProcessOutline of a Systematic ApproachRandom Phenomena, Variability, and UncertaintyTwo Extreme Idealizations of Natural PhenomenaRandom Mass PhenomenaIntroducing ProbabilityThe Probabilistic FrameworkII ProbabilityFundamentals of Probability TheoryBuilding BlocksOperationsProbabilityConditional ProbabilityIndependenceRandom Variables and DistributionsDistributionsMathematical ExpectationCharacterizing DistributionsSpecial Derived Probability FunctionsMultidimensional Random VariablesDistributions of Several Random VariablesDistributional Characteristics of Jointly Distributed Random VariablesRandom Variable TransformationsSingle Variable TransformationsBivariate TransformationsGeneral Multivariate TransformationsApplication Case Studies I: ProbabilityMendel and HeredityWorld War II Warship Tactical Response Under AttackIII DistributionsIde...

The Effects of Framing, Reflection, Probability, and Payoff on Risk Preference in Choice Tasks.

Science.gov (United States)

Kühberger; Schulte-Mecklenbeck; Perner

1999-06-01

A meta-analysis of Asian-disease-like studies is presented to identify the factors which determine risk preference. First the confoundings between probability levels, payoffs, and framing conditions are clarified in a task analysis. Then the role of framing, reflection, probability, type, and size of payoff is evaluated in a meta-analysis. It is shown that bidirectional framing effects exist for gains and for losses. Presenting outcomes as gains tends to induce risk aversion, while presenting outcomes as losses tends to induce risk seeking. Risk preference is also shown to depend on the size of the payoffs, on the probability levels, and on the type of good at stake (money/property vs human lives). In general, higher payoffs lead to increasing risk aversion. Higher probabilities lead to increasing risk aversion for gains and to increasing risk seeking for losses. These findings are confirmed by a subsequent empirical test. Shortcomings of existing formal theories, such as prospect theory, cumulative prospect theory, venture theory, and Markowitz's utility theory, are identified. It is shown that it is not probabilities or payoffs, but the framing condition, which explains most variance. These findings are interpreted as showing that no linear combination of formally relevant predictors is sufficient to capture the essence of the framing phenomenon. Copyright 1999 Academic Press.

Measure and integration theory

CERN Document Server

Burckel, Robert B

2001-01-01

This book gives a straightforward introduction to the field as it is nowadays required in many branches of analysis and especially in probability theory. The first three chapters (Measure Theory, Integration Theory, Product Measures) basically follow the clear and approved exposition given in the author's earlier book on ""Probability Theory and Measure Theory"". Special emphasis is laid on a complete discussion of the transformation of measures and integration with respect to the product measure, convergence theorems, parameter depending integrals, as well as the Radon-Nikodym theorem. The fi

Transition probability spaces in loop quantum gravity

Science.gov (United States)

Guo, Xiao-Kan

2018-03-01

We study the (generalized) transition probability spaces, in the sense of Mielnik and Cantoni, for spacetime quantum states in loop quantum gravity. First, we show that loop quantum gravity admits the structures of transition probability spaces. This is exemplified by first checking such structures in covariant quantum mechanics and then identifying the transition probability spaces in spin foam models via a simplified version of general boundary formulation. The transition probability space thus defined gives a simple way to reconstruct the discrete analog of the Hilbert space of the canonical theory and the relevant quantum logical structures. Second, we show that the transition probability space and in particular the spin foam model are 2-categories. Then we discuss how to realize in spin foam models two proposals by Crane about the mathematical structures of quantum gravity, namely, the quantum topos and causal sites. We conclude that transition probability spaces provide us with an alternative framework to understand various foundational questions of loop quantum gravity.

Knowledge typology for imprecise probabilities.

Energy Technology Data Exchange (ETDEWEB)

Wilson, G. D. (Gregory D.); Zucker, L. J. (Lauren J.)

2002-01-01

When characterizing the reliability of a complex system there are often gaps in the data available for specific subsystems or other factors influencing total system reliability. At Los Alamos National Laboratory we employ ethnographic methods to elicit expert knowledge when traditional data is scarce. Typically, we elicit expert knowledge in probabilistic terms. This paper will explore how we might approach elicitation if methods other than probability (i.e., Dempster-Shafer, or fuzzy sets) prove more useful for quantifying certain types of expert knowledge. Specifically, we will consider if experts have different types of knowledge that may be better characterized in ways other than standard probability theory.

Exact Symbol Error Probability of Square M-QAM Signaling over Generalized Fading Channels subject to Additive Generalized Gaussian Noise

KAUST Repository

Soury, Hamza

2013-07-01

This paper considers the average symbol error probability of square Quadrature Amplitude Modulation (QAM) coherent signaling over flat fading channels subject to additive generalized Gaussian noise. More specifically, a generic closedform expression in terms of the Fox H function and the bivariate Fox H function is offered for the extended generalized-K fading case. Simplifications for some special fading distributions such as generalized-K fading, Nakagami-m fading, and Rayleigh fading and special additive noise distributions such as Gaussian and Laplacian noise are then presented. Finally, the mathematical formalism is illustrated by some numerical examples verified by computer based simulations for a variety of fading and additive noise parameters.

Probability and statistics for particle physics

CERN Document Server

Mana, Carlos

2017-01-01

This book comprehensively presents the basic concepts of probability and Bayesian inference with sufficient generality to make them applicable to current problems in scientific research. The first chapter provides the fundamentals of probability theory that are essential for the analysis of random phenomena. The second chapter includes a full and pragmatic review of the Bayesian methods that constitute a natural and coherent framework with enough freedom to analyze all the information available from experimental data in a conceptually simple manner. The third chapter presents the basic Monte Carlo techniques used in scientific research, allowing a large variety of problems to be handled difficult to tackle by other procedures. The author also introduces a basic algorithm, which enables readers to simulate samples from simple distribution, and describes useful cases for researchers in particle physics.The final chapter is devoted to the basic ideas of Information Theory, which are important in the Bayesian me...

A large deformation theory of solids subject to electromagnetic loads and its application

International Nuclear Information System (INIS)

Nishiguchi, I.; Sasaki, M.

1993-01-01

A large deformation theory of deformable solids is proposed in which the interaction with electromagnetic fields is taken into account. Weak forms of the Maxwell's equations in a fixed reference configuration together with the balance of momentum constitute the governing equations for our theory. The weak forms of the Maxwell's equations in a reference configuration can be derived by the direct transformation from spatial weak forms. The results coincide with the weak forms obtained from the local expressions by Lax and Nelson though we made a distinction between the covariant and contravariant vector explicitly. For the deformable body subject to the electromagnetic fields, weak forms of the Ampere's law and/or the Faraday's law, when combined with the weak form of the balance of momentum, can serve as the governing equations of the theory. As is known, however, these equations are not sufficient to describe the response of a specific material due to a given loading. As for the momentum balance, we need the dependency of stress on the deformation and objective constitutive equations of hyperelasticity, hypoelasticity and inelasticity are available. Parallel to these, objective constitutive equations for the electromagnetism are discussed. As an application of the theory, linearized equations for quasi-static deformation under magnetic field is derived based on the vector potential formulation. (author)

Stochastics introduction to probability and statistics

CERN Document Server

Georgii, Hans-Otto

2012-01-01

This second revised and extended edition presents the fundamental ideas and results of both, probability theory and statistics, and comprises the material of a one-year course. It is addressed to students with an interest in the mathematical side of stochastics. Stochastic concepts, models and methods are motivated by examples and developed and analysed systematically. Some measure theory is included, but this is done at an elementary level that is in accordance with the introductory character of the book. A large number of problems offer applications and supplements to the text.

Sociological theories of subjective well-being

NARCIS (Netherlands)

R. Veenhoven (Ruut)

2009-01-01

textabstractSubjective well-being is no great issue in sociology; the subject is not mentioned in sociological textbooks (a notable exception is Nolan & Lenski, 2004) and is rarely discussed in sociological journals. This absence has many reasons: pragmatic, ideological, and theoretical. To begin

Multiple-event probability in general-relativistic quantum mechanics

International Nuclear Information System (INIS)

Hellmann, Frank; Mondragon, Mauricio; Perez, Alejandro; Rovelli, Carlo

2007-01-01

We discuss the definition of quantum probability in the context of 'timeless' general-relativistic quantum mechanics. In particular, we study the probability of sequences of events, or multievent probability. In conventional quantum mechanics this can be obtained by means of the 'wave function collapse' algorithm. We first point out certain difficulties of some natural definitions of multievent probability, including the conditional probability widely considered in the literature. We then observe that multievent probability can be reduced to single-event probability, by taking into account the quantum nature of the measuring apparatus. In fact, by exploiting the von-Neumann freedom of moving the quantum/classical boundary, one can always trade a sequence of noncommuting quantum measurements at different times, with an ensemble of simultaneous commuting measurements on the joint system+apparatus system. This observation permits a formulation of quantum theory based only on single-event probability, where the results of the wave function collapse algorithm can nevertheless be recovered. The discussion also bears on the nature of the quantum collapse

Stochastic calculus an introduction through theory and exercises

CERN Document Server

Baldi, Paolo

2017-01-01

This book provides a comprehensive introduction to the theory of stochastic calculus and some of its applications. It is the only textbook on the subject to include more than two hundred exercises with complete solutions. After explaining the basic elements of probability, the author introduces more advanced topics such as Brownian motion, martingales and Markov processes. The core of the book covers stochastic calculus, including stochastic differential equations, the relationship to partial differential equations, numerical methods and simulation, as well as applications of stochastic processes to finance. The final chapter provides detailed solutions to all exercises, in some cases presenting various solution techniques together with a discussion of advantages and drawbacks of the methods used. Stochastic Calculus will be particularly useful to advanced undergraduate and graduate students wishing to acquire a solid understanding of the subject through the theory and exercises. Including full mathematical ...

The Problem of Probability: An Examination and Refutation of Hjørland’s Relevance Equation

DEFF Research Database (Denmark)

Nicolaisen, Jeppe

2017-01-01

Introduction. The paper presents a critical examination of Professor Birger Hjørland’s relevance equation: Something (A) is relevant to a task (T) if it increases the likelihood of accomplishing the goal (G), which is implied by T. Method. Two theories of probability logic (the logical theory...... and the intersubjective theory) are briefly reviewed and then applied to Hjørland’s equation. Analysis. Focusing on how these theories warrant the probability assumption makes it possible to detect deficiencies in Hjørland’s equation, based as it is on probability logic. Results. Regardless of the kind of logic applied...... to warrant the probability assumption of Hjørland’s equation, the outcome of using it to determine the relevance of any A to any T is found to have quite bizarre consequences: Either nothing is relevant or everything is relevant. Conclusion. Contrary to Hjørland’s claim that his relevance equation applies...

Imprecise Probability Methods for Weapons UQ

Energy Technology Data Exchange (ETDEWEB)

Picard, Richard Roy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Vander Wiel, Scott Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-05-13

Building on recent work in uncertainty quanti cation, we examine the use of imprecise probability methods to better characterize expert knowledge and to improve on misleading aspects of Bayesian analysis with informative prior distributions. Quantitative approaches to incorporate uncertainties in weapons certi cation are subject to rigorous external peer review, and in this regard, certain imprecise probability methods are well established in the literature and attractive. These methods are illustrated using experimental data from LANL detonator impact testing.

AN EDUCATIONAL THEORY MODEL--(SIGGS), AN INTEGRATION OF SET THEORY, INFORMATION THEORY, AND GRAPH THEORY WITH GENERAL SYSTEMS THEORY.

Science.gov (United States)

MACCIA, ELIZABETH S.; AND OTHERS

AN ANNOTATED BIBLIOGRAPHY OF 20 ITEMS AND A DISCUSSION OF ITS SIGNIFICANCE WAS PRESENTED TO DESCRIBE CURRENT UTILIZATION OF SUBJECT THEORIES IN THE CONSTRUCTION OF AN EDUCATIONAL THEORY. ALSO, A THEORY MODEL WAS USED TO DEMONSTRATE CONSTRUCTION OF A SCIENTIFIC EDUCATIONAL THEORY. THE THEORY MODEL INCORPORATED SET THEORY (S), INFORMATION THEORY…

Probability and Statistics The Science of Uncertainty (Revised Edition)

CERN Document Server

Tabak, John

2011-01-01

Probability and Statistics, Revised Edition deals with the history of probability, describing the modern concept of randomness and examining "pre-probabilistic" ideas of what most people today would characterize as randomness. This revised book documents some historically important early uses of probability to illustrate some very important probabilistic questions. It goes on to explore statistics and the generations of mathematicians and non-mathematicians who began to address problems in statistical analysis, including the statistical structure of data sets as well as the theory of

Spectral analysis of growing graphs a quantum probability point of view

CERN Document Server

Obata, Nobuaki

2017-01-01

This book is designed as a concise introduction to the recent achievements on spectral analysis of graphs or networks from the point of view of quantum (or non-commutative) probability theory. The main topics are spectral distributions of the adjacency matrices of finite or infinite graphs and their limit distributions for growing graphs. The main vehicle is quantum probability, an algebraic extension of the traditional probability theory, which provides a new framework for the analysis of adjacency matrices revealing their non-commutative nature. For example, the method of quantum decomposition makes it possible to study spectral distributions by means of interacting Fock spaces or equivalently by orthogonal polynomials. Various concepts of independence in quantum probability and corresponding central limit theorems are used for the asymptotic study of spectral distributions for product graphs. This book is written for researchers, teachers, and students interested in graph spectra, their (asymptotic) spectr...

Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

International Nuclear Information System (INIS)

Helton, J.C.

1996-03-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S st , S st , p st ) for stochastic uncertainty, a probability space (S su , S su , p su ) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S st , S st , p st ) and (S su , S su , p su ). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the U.S. Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems

Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

International Nuclear Information System (INIS)

Helton, J.C.

1996-01-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S st , L st , P st ) for stochastic uncertainty, a probability space (S su , L su , P su ) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S st , L st , P st ) and (S su , L su , P su ). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the US Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems

Quantum theory of measurements as quantum decision theory

International Nuclear Information System (INIS)

Yukalov, V I; Sornette, D

2015-01-01

Theory of quantum measurements is often classified as decision theory. An event in decision theory corresponds to the measurement of an observable. This analogy looks clear for operationally testable simple events. However, the situation is essentially more complicated in the case of composite events. The most difficult point is the relation between decisions under uncertainty and measurements under uncertainty. We suggest a unified language for describing the processes of quantum decision making and quantum measurements. The notion of quantum measurements under uncertainty is introduced. We show that the correct mathematical foundation for the theory of measurements under uncertainty, as well as for quantum decision theory dealing with uncertain events, requires the use of positive operator-valued measure that is a generalization of projection-valued measure. The latter is appropriate for operationally testable events, while the former is necessary for characterizing operationally uncertain events. In both decision making and quantum measurements, one has to distinguish composite nonentangled events from composite entangled events. Quantum probability can be essentially different from classical probability only for entangled events. The necessary condition for the appearance of an interference term in the quantum probability is the occurrence of entangled prospects and the existence of an entangled strategic state of a decision maker or of an entangled statistical state of a measuring device

Conditional probability on MV-algebras

Czech Academy of Sciences Publication Activity Database

Kroupa, Tomáš

2005-01-01

Roč. 149, č. 2 (2005), s. 369-381 ISSN 0165-0114 R&D Projects: GA AV ČR IAA2075302 Institutional research plan: CEZ:AV0Z10750506 Keywords : conditional probability * tribe * MV-algebra Subject RIV: BA - General Mathematics Impact factor: 1.039, year: 2005

Blind source separation theory and applications

CERN Document Server

Yu, Xianchuan; Xu, Jindong

2013-01-01

A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies    The book presents an overview of Blind Source Separation, a relatively new signal processing method.  Due to the multidisciplinary nature of the subject, the book has been written so as to appeal to an audience from very different backgrounds. Basic mathematical skills (e.g. on matrix algebra and foundations of probability theory) are essential in order to understand the algorithms, although the book is written in an introductory, accessible style. This book offers

Has David Howden Vindicated Richard von Mises’s Definition of Probability?

Directory of Open Access Journals (Sweden)

Mark R. Crovelli

2009-11-01

Full Text Available In my recent article on these pages (Crovelli 2009 I argued that members of the Austrian School of economics have adopted and defended a faulty definition of probability. I argued that the definition of probability necessarily depends upon the nature of the world in which we live. I claimed that if the nature of the world is such that every event and phenomenon which occurs has a cause of some sort, then probability must be defined subjectively; that is, “as a measure of our uncertainty about the likelihood of occurrence of some event or phenomenon, based upon evidence that need not derive solely from past frequencies of ‘collectives’ or ‘classes.’” I further claimed that the nature of the world is indeed such that all events and phenomena have prior causes, and that this fact compels us to adopt a subjective definition of probability.David Howden has recently published what he claims is a refutation of my argument in his article “Single Trial Probability Applications: Can Subjectivity Evade Frequency Limitations” (Howden 2009. Unfortunately, Mr. Howden appears to not have understood my argument, and his purported refutation of my subjective definition consequently amounts to nothing more than a concatenation of confused and fallacious ideas that are completely irrelevant to my argument. David Howden has thus failed in his attempt to vindicate Richard von Mises’s definition of probability.

Decision making with consonant belief functions: Discrepancy resulting with the probability transformation method used

Directory of Open Access Journals (Sweden)

Cinicioglu Esma Nur

2014-01-01

Full Text Available Dempster−Shafer belief function theory can address a wider class of uncertainty than the standard probability theory does, and this fact appeals the researchers in operations research society for potential application areas. However, the lack of a decision theory of belief functions gives rise to the need to use the probability transformation methods for decision making. For representation of statistical evidence, the class of consonant belief functions is used which is not closed under Dempster’s rule of combination but is closed under Walley’s rule of combination. In this research, it is shown that the outcomes obtained using both Dempster’s and Walley’s rules do result in different probability distributions when pignistic transformation is used. However, when plausibility transformation is used, they do result in the same probability distribution. This result shows that the choice of the combination rule and probability transformation method may have a significant effect on decision making since it may change the choice of the decision alternative selected. This result is illustrated via an example of missile type identification.

On the structure of the quantum-mechanical probability models

International Nuclear Information System (INIS)

Cufaro-Petroni, N.

1992-01-01

In this paper the role of the mathematical probability models in the classical and quantum physics in shortly analyzed. In particular the formal structure of the quantum probability spaces (QPS) is contrasted with the usual Kolmogorovian models of probability by putting in evidence the connections between this structure and the fundamental principles of the quantum mechanics. The fact that there is no unique Kolmogorovian model reproducing a QPS is recognized as one of the main reasons of the paradoxical behaviors pointed out in the quantum theory from its early days. 8 refs

Normal probability plots with confidence.

Science.gov (United States)

Chantarangsi, Wanpen; Liu, Wei; Bretz, Frank; Kiatsupaibul, Seksan; Hayter, Anthony J; Wan, Fang

2015-01-01

Normal probability plots are widely used as a statistical tool for assessing whether an observed simple random sample is drawn from a normally distributed population. The users, however, have to judge subjectively, if no objective rule is provided, whether the plotted points fall close to a straight line. In this paper, we focus on how a normal probability plot can be augmented by intervals for all the points so that, if the population distribution is normal, then all the points should fall into the corresponding intervals simultaneously with probability 1-α. These simultaneous 1-α probability intervals provide therefore an objective mean to judge whether the plotted points fall close to the straight line: the plotted points fall close to the straight line if and only if all the points fall into the corresponding intervals. The powers of several normal probability plot based (graphical) tests and the most popular nongraphical Anderson-Darling and Shapiro-Wilk tests are compared by simulation. Based on this comparison, recommendations are given in Section 3 on which graphical tests should be used in what circumstances. An example is provided to illustrate the methods. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Log-concave Probability Distributions: Theory and Statistical Testing

DEFF Research Database (Denmark)

An, Mark Yuing

1996-01-01

This paper studies the broad class of log-concave probability distributions that arise in economics of uncertainty and information. For univariate, continuous, and log-concave random variables we prove useful properties without imposing the differentiability of density functions. Discrete...... and multivariate distributions are also discussed. We propose simple non-parametric testing procedures for log-concavity. The test statistics are constructed to test one of the two implicati ons of log-concavity: increasing hazard rates and new-is-better-than-used (NBU) property. The test for increasing hazard...... rates are based on normalized spacing of the sample order statistics. The tests for NBU property fall into the category of Hoeffding's U-statistics...

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

Science.gov (United States)

Doubravsky, Karel; Dohnal, Mirko

2015-01-01

Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

Directory of Open Access Journals (Sweden)

Karel Doubravsky

Full Text Available Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (rechecked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.

Key Informant Models for Measuring Group-Level Variables in Small Groups: Application to Plural Subject Theory

Science.gov (United States)

Algesheimer, René; Bagozzi, Richard P.; Dholakia, Utpal M.

2018-01-01

We offer a new conceptualization and measurement models for constructs at the group-level of analysis in small group research. The conceptualization starts with classical notions of group behavior proposed by Tönnies, Simmel, and Weber and then draws upon plural subject theory by philosophers Gilbert and Tuomela to frame a new perspective…

On New Cautious Structural Reliability Models in the Framework of imprecise Probabilities

DEFF Research Database (Denmark)

Utkin, Lev V.; Kozine, Igor

2010-01-01

models and gen-eralizing conventional ones to imprecise probabili-ties. The theoretical setup employed for this purpose is imprecise statistical reasoning (Walley 1991), whose general framework is provided by upper and lower previsions (expectations). The appeal of this theory is its ability to capture......Uncertainty of parameters in engineering design has been modeled in different frameworks such as inter-val analysis, fuzzy set and possibility theories, ran-dom set theory and imprecise probability theory. The authors of this paper for many years have been de-veloping new imprecise reliability...... both aleatory (stochas-tic) and epistemic uncertainty and the flexibility with which information can be represented. The previous research of the authors related to generalizing structural reliability models to impre-cise statistical measures is summarized in Utkin & Kozine (2002) and Utkin (2004...

Logic, Probability, and Human Reasoning

Science.gov (United States)

2015-01-01

accordingly suggest a way to integrate probability and deduction. The nature of deductive reasoning To be rational is to be able to make deductions...3–6] and they underlie mathematics, science, and tech- nology [7–10]. Plato claimed that emotions upset reason- ing. However, individuals in the grip...fundamental to human rationality . So, if counterexamples to its principal predictions occur, the theory will at least explain its own refutation

Fixation Probability in a Haploid-Diploid Population.

Science.gov (United States)

Bessho, Kazuhiro; Otto, Sarah P

2017-01-01

Classical population genetic theory generally assumes either a fully haploid or fully diploid life cycle. However, many organisms exhibit more complex life cycles, with both free-living haploid and diploid stages. Here we ask what the probability of fixation is for selected alleles in organisms with haploid-diploid life cycles. We develop a genetic model that considers the population dynamics using both the Moran model and Wright-Fisher model. Applying a branching process approximation, we obtain an accurate fixation probability assuming that the population is large and the net effect of the mutation is beneficial. We also find the diffusion approximation for the fixation probability, which is accurate even in small populations and for deleterious alleles, as long as selection is weak. These fixation probabilities from branching process and diffusion approximations are similar when selection is weak for beneficial mutations that are not fully recessive. In many cases, particularly when one phase predominates, the fixation probability differs substantially for haploid-diploid organisms compared to either fully haploid or diploid species. Copyright © 2017 by the Genetics Society of America.

Neutron emission probability at high excitation and isospin

International Nuclear Information System (INIS)

Aggarwal, Mamta

2005-01-01

One-neutron and two-neutron emission probability at different excitations and varying isospin have been studied. Several degrees of freedom like deformation, rotations, temperature, isospin fluctuations and shell structure are incorporated via statistical theory of hot rotating nuclei

Frame representations of quantum mechanics and the necessity of negativity in quasi-probability representations

International Nuclear Information System (INIS)

Ferrie, Christopher; Emerson, Joseph

2008-01-01

Several finite-dimensional quasi-probability representations of quantum states have been proposed to study various problems in quantum information theory and quantum foundations. These representations are often defined only on restricted dimensions and their physical significance in contexts such as drawing quantum-classical comparisons is limited by the non-uniqueness of the particular representation. Here we show how the mathematical theory of frames provides a unified formalism which accommodates all known quasi-probability representations of finite-dimensional quantum systems. Moreover, we show that any quasi-probability representation is equivalent to a frame representation and then prove that any such representation of quantum mechanics must exhibit either negativity or a deformed probability calculus. (fast track communication)

Probability, statistics, and associated computing techniques

International Nuclear Information System (INIS)

James, F.

1983-01-01

This chapter attempts to explore the extent to which it is possible for the experimental physicist to find optimal statistical techniques to provide a unique and unambiguous quantitative measure of the significance of raw data. Discusses statistics as the inverse of probability; normal theory of parameter estimation; normal theory (Gaussian measurements); the universality of the Gaussian distribution; real-life resolution functions; combination and propagation of uncertainties; the sum or difference of 2 variables; local theory, or the propagation of small errors; error on the ratio of 2 discrete variables; the propagation of large errors; confidence intervals; classical theory; Bayesian theory; use of the likelihood function; the second derivative of the log-likelihood function; multiparameter confidence intervals; the method of MINOS; least squares; the Gauss-Markov theorem; maximum likelihood for uniform error distribution; the Chebyshev fit; the parameter uncertainties; the efficiency of the Chebyshev estimator; error symmetrization; robustness vs. efficiency; testing of hypotheses (e.g., the Neyman-Pearson test); goodness-of-fit; distribution-free tests; comparing two one-dimensional distributions; comparing multidimensional distributions; and permutation tests for comparing two point sets

Predictive probability methods for interim monitoring in clinical trials with longitudinal outcomes.

Science.gov (United States)

Zhou, Ming; Tang, Qi; Lang, Lixin; Xing, Jun; Tatsuoka, Kay

2018-04-17

In clinical research and development, interim monitoring is critical for better decision-making and minimizing the risk of exposing patients to possible ineffective therapies. For interim futility or efficacy monitoring, predictive probability methods are widely adopted in practice. Those methods have been well studied for univariate variables. However, for longitudinal studies, predictive probability methods using univariate information from only completers may not be most efficient, and data from on-going subjects can be utilized to improve efficiency. On the other hand, leveraging information from on-going subjects could allow an interim analysis to be potentially conducted once a sufficient number of subjects reach an earlier time point. For longitudinal outcomes, we derive closed-form formulas for predictive probabilities, including Bayesian predictive probability, predictive power, and conditional power and also give closed-form solutions for predictive probability of success in a future trial and the predictive probability of success of the best dose. When predictive probabilities are used for interim monitoring, we study their distributions and discuss their analytical cutoff values or stopping boundaries that have desired operating characteristics. We show that predictive probabilities utilizing all longitudinal information are more efficient for interim monitoring than that using information from completers only. To illustrate their practical application for longitudinal data, we analyze 2 real data examples from clinical trials. Copyright © 2018 John Wiley & Sons, Ltd.

Geometric modeling in probability and statistics

CERN Document Server

Calin, Ovidiu

2014-01-01

This book covers topics of Informational Geometry, a field which deals with the differential geometric study of the manifold probability density functions. This is a field that is increasingly attracting the interest of researchers from many different areas of science, including mathematics, statistics, geometry, computer science, signal processing, physics and neuroscience. It is the authors’ hope that the present book will be a valuable reference for researchers and graduate students in one of the aforementioned fields. This textbook is a unified presentation of differential geometry and probability theory, and constitutes a text for a course directed at graduate or advanced undergraduate students interested in applications of differential geometry in probability and statistics. The book contains over 100 proposed exercises meant to help students deepen their understanding, and it is accompanied by software that is able to provide numerical computations of several information geometric objects. The reader...

Prospect evaluation as a function of numeracy and probability denominator.

Science.gov (United States)

Millroth, Philip; Juslin, Peter

2015-05-01

This study examines how numeracy and probability denominator (a direct-ratio probability, a relative frequency with denominator 100, a relative frequency with denominator 10,000) affect the evaluation of prospects in an expected-value based pricing task. We expected that numeracy would affect the results due to differences in the linearity of number perception and the susceptibility to denominator neglect with different probability formats. An analysis with functional measurement verified that participants integrated value and probability into an expected value. However, a significant interaction between numeracy and probability format and subsequent analyses of the parameters of cumulative prospect theory showed that the manipulation of probability denominator changed participants' psychophysical response to probability and value. Standard methods in decision research may thus confound people's genuine risk attitude with their numerical capacities and the probability format used. Copyright © 2015 Elsevier B.V. All rights reserved.

Probability, random processes, and ergodic properties

CERN Document Server

Gray, Robert M

1988-01-01

This book has been written for several reasons, not all of which are academic. This material was for many years the first half of a book in progress on information and ergodic theory. The intent was and is to provide a reasonably self-contained advanced treatment of measure theory, prob ability theory, and the theory of discrete time random processes with an emphasis on general alphabets and on ergodic and stationary properties of random processes that might be neither ergodic nor stationary. The intended audience was mathematically inc1ined engineering graduate students and visiting scholars who had not had formal courses in measure theoretic probability . Much of the material is familiar stuff for mathematicians, but many of the topics and results have not previously appeared in books. The original project grew too large and the first part contained much that would likely bore mathematicians and dis courage them from the second part. Hence I finally followed the suggestion to separate the material and split...

Applied probability and stochastic processes. 2. ed.

Energy Technology Data Exchange (ETDEWEB)

Feldman, Richard M. [Texas A and M Univ., College Station, TX (United States). Industrial and Systems Engineering Dept.; Valdez-Flores, Ciriaco [Sielken and Associates Consulting, Inc., Bryan, TX (United States)

2010-07-01

This book presents applied probability and stochastic processes in an elementary but mathematically precise manner, with numerous examples and exercises to illustrate the range of engineering and science applications of the concepts. The book is designed to give the reader an intuitive understanding of probabilistic reasoning, in addition to an understanding of mathematical concepts and principles. The initial chapters present a summary of probability and statistics and then Poisson processes, Markov chains, Markov processes and queuing processes are introduced. Advanced topics include simulation, inventory theory, replacement theory, Markov decision theory, and the use of matrix geometric procedures in the analysis of queues. Included in the second edition are appendices at the end of several chapters giving suggestions for the use of Excel in solving the problems of the chapter. Also new in this edition are an introductory chapter on statistics and a chapter on Poisson processes that includes some techniques used in risk assessment. The old chapter on queues has been expanded and broken into two new chapters: one for simple queuing processes and one for queuing networks. Support is provided through the web site http://apsp.tamu.edu where students will have the answers to odd numbered problems and instructors will have access to full solutions and Excel files for homework. (orig.)

Exaggerated Risk: Prospect Theory and Probability Weighting in Risky Choice

Science.gov (United States)

Kusev, Petko; van Schaik, Paul; Ayton, Peter; Dent, John; Chater, Nick

2009-01-01

In 5 experiments, we studied precautionary decisions in which participants decided whether or not to buy insurance with specified cost against an undesirable event with specified probability and cost. We compared the risks taken for precautionary decisions with those taken for equivalent monetary gambles. Fitting these data to Tversky and…

Probability, conditional probability and complementary cumulative distribution functions in performance assessment for radioactive waste disposal

Energy Technology Data Exchange (ETDEWEB)

Helton, J.C. [Arizona State Univ., Tempe, AZ (United States)

1996-03-01

A formal description of the structure of several recent performance assessments (PAs) for the Waste Isolation Pilot Plant (WIPP) is given in terms of the following three components: a probability space (S{sub st}, S{sub st}, p{sub st}) for stochastic uncertainty, a probability space (S{sub su}, S{sub su}, p{sub su}) for subjective uncertainty and a function (i.e., a random variable) defined on the product space associated with (S{sub st}, S{sub st}, p{sub st}) and (S{sub su}, S{sub su}, p{sub su}). The explicit recognition of the existence of these three components allows a careful description of the use of probability, conditional probability and complementary cumulative distribution functions within the WIPP PA. This usage is illustrated in the context of the U.S. Environmental Protection Agency`s standard for the geologic disposal of radioactive waste (40 CFR 191, Subpart B). The paradigm described in this presentation can also be used to impose a logically consistent structure on PAs for other complex systems.

Response to Yellman and Murray's comment on 'The meaning of probability in probabilistic risk analysis'

International Nuclear Information System (INIS)

Watson, Stephen R.

1995-01-01

In their comment on a recent contribution of mine, [Watson, S., The meaning of probability in probabilistic safety analysis. Reliab. Engng and System Safety, 45 (1994) 261-269.] Yellman and Murray assert that (1) I argue in favour of a realistic interpretation of probability for PSAs; (2) that the only satisfactory philosophical theory of probability is the relative frequency theory; (3) that I mean the same thing by the words 'uncertainty' and 'probability'; (4) that my argument can easily lead to the belief that the output of PSAs are meaningless. I take issue with all these points, and in this response I set out my arguments

Targeting the probability versus cost of feared outcomes in public speaking anxiety.

Science.gov (United States)

Nelson, Elizabeth A; Deacon, Brett J; Lickel, James J; Sy, Jennifer T

2010-04-01

Cognitive-behavioral theory suggests that social phobia is maintained, in part, by overestimates of the probability and cost of negative social events. Indeed, empirically supported cognitive-behavioral treatments directly target these cognitive biases through the use of in vivo exposure or behavioral experiments. While cognitive-behavioral theories and treatment protocols emphasize the importance of targeting probability and cost biases in the reduction of social anxiety, few studies have examined specific techniques for reducing probability and cost bias, and thus the relative efficacy of exposure to the probability versus cost of negative social events is unknown. In the present study, 37 undergraduates with high public speaking anxiety were randomly assigned to a single-session intervention designed to reduce either the perceived probability or the perceived cost of negative outcomes associated with public speaking. Compared to participants in the probability treatment condition, those in the cost treatment condition demonstrated significantly greater improvement on measures of public speaking anxiety and cost estimates for negative social events. The superior efficacy of the cost treatment condition was mediated by greater treatment-related changes in social cost estimates. The clinical implications of these findings are discussed. Published by Elsevier Ltd.

Probability concepts in quality risk management.

Science.gov (United States)

Claycamp, H Gregg

2012-01-01

Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although risk is generally a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management tools are relatively silent on the meaning and uses of "probability." The probability concept is typically applied by risk managers as a combination of frequency-based calculation and a "degree of belief" meaning of probability. Probability as a concept that is crucial for understanding and managing risk is discussed through examples from the most general, scenario-defining and ranking tools that use probability implicitly to more specific probabilistic tools in risk management. A rich history of probability in risk management applied to other fields suggests that high-quality risk management decisions benefit from the implementation of more thoughtful probability concepts in both risk modeling and risk management. Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although "risk" generally describes a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management methodologies and respective tools focus on managing severity but are relatively silent on the in-depth meaning and uses of "probability." Pharmaceutical manufacturers are expanding their use of quality risk management to identify and manage risks to the patient that might occur in phases of the pharmaceutical life cycle from drug development to manufacture, marketing to product discontinuation. A probability concept is typically applied by risk managers as a combination of data-based measures of probability and a subjective "degree of belief" meaning of probability. Probability as

Probabilities, causes and propensities in physics

CERN Document Server

Suárez, Mauricio

2010-01-01

This volume defends a novel approach to the philosophy of physics: it is the first book devoted to a comparative study of probability, causality, and propensity, and their various interrelations, within the context of contemporary physics - particularly quantum and statistical physics. The philosophical debates and distinctions are firmly grounded upon examples from actual physics, thus exemplifying a robustly empiricist approach. The essays, by both prominent scholars in the field and promising young researchers, constitute a pioneer effort in bringing out the connections between probabilistic, causal and dispositional aspects of the quantum domain. This book will appeal to specialists in philosophy and foundations of physics, philosophy of science in general, metaphysics, ontology of physics theories, and philosophy of probability.

An analytic approach to probability tables for the unresolved resonance region

Science.gov (United States)

Brown, David; Kawano, Toshihiko

2017-09-01

The Unresolved Resonance Region (URR) connects the fast neutron region with the Resolved Resonance Region (RRR). The URR is problematic since resonances are not resolvable experimentally yet the fluctuations in the neutron cross sections play a discernible and technologically important role: the URR in a typical nucleus is in the 100 keV - 2 MeV window where the typical fission spectrum peaks. The URR also represents the transition between R-matrix theory used to described isolated resonances and Hauser-Feshbach theory which accurately describes the average cross sections. In practice, only average or systematic features of the resonances in the URR are known and are tabulated in evaluations in a nuclear data library such as ENDF/B-VII.1. Codes such as AMPX and NJOY can compute the probability distribution of the cross section in the URR under some assumptions using Monte Carlo realizations of sets of resonances. These probability distributions are stored in the so-called PURR tables. In our work, we begin to develop a scheme for computing the covariance of the cross section probability distribution analytically. Our approach offers the possibility of defining the limits of applicability of Hauser-Feshbach theory and suggests a way to calculate PURR tables directly from systematics for nuclei whose RRR is unknown, provided one makes appropriate assumptions about the shape of the cross section probability distribution.

Probability in High Dimension

Science.gov (United States)

2014-06-30

precisely the content of the following result. The price we pay is that the assumption that A is a packing in (F, k ·k1) is too weak to make this happen...Regularité des trajectoires des fonctions aléatoires gaussiennes. In: École d’Été de Probabilités de Saint- Flour , IV-1974, pp. 1–96. Lecture Notes in...Lectures on probability theory and statistics (Saint- Flour , 1994), Lecture Notes in Math., vol. 1648, pp. 165–294. Springer, Berlin (1996) 50. Ledoux

First-passage probability of the deflection of a cable-stayed bridge under long-term site-specific traffic loading

Directory of Open Access Journals (Sweden)

Naiwei Lu

2017-01-01

Full Text Available Long-span bridges suffer from higher traffic loads and the simultaneous presence of multiple vehicles, which in conjunction with the steady traffic growth may pose a threat to the bridge safety. This study presents a methodology for first-passage probability evaluation of long-span bridges subject to stochastic heavy traffic loading. Initially, the stochastic heavy traffic loading was simulated based on long-term weigh-in-motion measurements of a highway bridge in China. A computational framework was presented integrating Rice’s level-crossing theory and the first-passage criterion. The effectiveness of the computational framework was demonstrated through a case study of a cable-stayed bridge. Numerical results show that the upper tail fitting of the up-crossing rate is an appropriate description of probability characteristics of the extreme traffic load effects of long-span bridges. The average daily truck traffic growth increases the probability of exceedance due to an intensive heavy traffic flow and results in a higher first-passage probability, but this increased trend is weakening as the continuous increase of the traffic volume. Since the sustained growth of gross vehicle weight has a constant impact on the probability of failure, setting a reasonable threshold overload ratio is an effective scheme as a traffic management to ensure the bridge serviceability.

Comment on 'The meaning of probability in probabilistic safety analysis'

International Nuclear Information System (INIS)

Yellman, Ted W.; Murray, Thomas M.

1995-01-01

A recent article in Reliability Engineering and System Safety argues that there is 'fundamental confusion over how to interpret the numbers which emerge from a Probabilistic Safety Analysis [PSA]', [Watson, S. R., The meaning of probability in probabilistic safety analysis. Reliab. Engng and System Safety, 45 (1994) 261-269.] As a standard for comparison, the author employs the 'realist' interpretation that a PSA output probability should be a 'physical property' of the installation being analyzed, 'objectively measurable' without controversy. The author finds all the other theories and philosophies discussed wanting by this standard. Ultimately, he argues that the outputs of a PSA should be considered to be no more than constructs of the computational procedure chosen - just an 'argument' or a 'framework for the debate about safety' rather than a 'representation of truth'. He even suggests that 'competing' PSA's be done - each trying to 'argue' for a different message. The commentors suggest that the position the author arrives at is an overreaction to the subjectivity which is part of any complex PSA, and that that overreaction could in fact easily lead to the belief that PSA's are meaningless. They suggest a broader interpretation, one based strictly on relative frequency--a concept which the commentors believe the author abandoned too quickly. Their interpretation does not require any 'tests' to determine whether a statement of likelihood is qualified to be a 'true' probability and it applies equally well in pure analytical models. It allows anyone's proper numerical statement of the likelihood of an event to be considered a probability. It recognizes that the quality of PSA's and their results will vary. But, unlike the author, the commentors contend that a PSA should always be a search for truth--not a vehicle for adversarial pleadings

Uncertainty plus prior equals rational bias: an intuitive Bayesian probability weighting function.

Science.gov (United States)

Fennell, John; Baddeley, Roland

2012-10-01

Empirical research has shown that when making choices based on probabilistic options, people behave as if they overestimate small probabilities, underestimate large probabilities, and treat positive and negative outcomes differently. These distortions have been modeled using a nonlinear probability weighting function, which is found in several nonexpected utility theories, including rank-dependent models and prospect theory; here, we propose a Bayesian approach to the probability weighting function and, with it, a psychological rationale. In the real world, uncertainty is ubiquitous and, accordingly, the optimal strategy is to combine probability statements with prior information using Bayes' rule. First, we show that any reasonable prior on probabilities leads to 2 of the observed effects; overweighting of low probabilities and underweighting of high probabilities. We then investigate 2 plausible kinds of priors: informative priors based on previous experience and uninformative priors of ignorance. Individually, these priors potentially lead to large problems of bias and inefficiency, respectively; however, when combined using Bayesian model comparison methods, both forms of prior can be applied adaptively, gaining the efficiency of empirical priors and the robustness of ignorance priors. We illustrate this for the simple case of generic good and bad options, using Internet blogs to estimate the relevant priors of inference. Given this combined ignorant/informative prior, the Bayesian probability weighting function is not only robust and efficient but also matches all of the major characteristics of the distortions found in empirical research. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Mathematical methods in the theory of queuing

CERN Document Server

Khinchin, A Y; Quenouille, M H

2013-01-01

Written by a prominent Russian mathematician, this concise monograph examines aspects of queuing theory as an application of probability. The three-part treatment begins with a study of the stream of incoming demands (or ""calls,"" in the author's terminology). Subsequent sections explore systems with losses and systems allowing delay. Prerequisites include a familiarity with the theory of probability and mathematical analysis. A. Y. Khinchin made significant contributions to probability theory, statistical physics, and several other fields. His elegant, groundbreaking work will prove of subs

Quantum Decision Theory in Simple Risky Choices.

Science.gov (United States)

Favre, Maroussia; Wittwer, Amrei; Heinimann, Hans Rudolf; Yukalov, Vyacheslav I; Sornette, Didier

2016-01-01

Quantum decision theory (QDT) is a recently developed theory of decision making based on the mathematics of Hilbert spaces, a framework known in physics for its application to quantum mechanics. This framework formalizes the concept of uncertainty and other effects that are particularly manifest in cognitive processes, which makes it well suited for the study of decision making. QDT describes a decision maker's choice as a stochastic event occurring with a probability that is the sum of an objective utility factor and a subjective attraction factor. QDT offers a prediction for the average effect of subjectivity on decision makers, the quarter law. We examine individual and aggregated (group) data, and find that the results are in good agreement with the quarter law at the level of groups. At the individual level, it appears that the quarter law could be refined in order to reflect individual characteristics. This article revisits the formalism of QDT along a concrete example and offers a practical guide to researchers who are interested in applying QDT to a dataset of binary lotteries in the domain of gains.

Transitional Probabilities Are Prioritized over Stimulus/Pattern Probabilities in Auditory Deviance Detection: Memory Basis for Predictive Sound Processing.

Science.gov (United States)

Mittag, Maria; Takegata, Rika; Winkler, István

2016-09-14

Representations encoding the probabilities of auditory events do not directly support predictive processing. In contrast, information about the probability with which a given sound follows another (transitional probability) allows predictions of upcoming sounds. We tested whether behavioral and cortical auditory deviance detection (the latter indexed by the mismatch negativity event-related potential) relies on probabilities of sound patterns or on transitional probabilities. We presented healthy adult volunteers with three types of rare tone-triplets among frequent standard triplets of high-low-high (H-L-H) or L-H-L pitch structure: proximity deviant (H-H-H/L-L-L), reversal deviant (L-H-L/H-L-H), and first-tone deviant (L-L-H/H-H-L). If deviance detection was based on pattern probability, reversal and first-tone deviants should be detected with similar latency because both differ from the standard at the first pattern position. If deviance detection was based on transitional probabilities, then reversal deviants should be the most difficult to detect because, unlike the other two deviants, they contain no low-probability pitch transitions. The data clearly showed that both behavioral and cortical auditory deviance detection uses transitional probabilities. Thus, the memory traces underlying cortical deviance detection may provide a link between stimulus probability-based change/novelty detectors operating at lower levels of the auditory system and higher auditory cognitive functions that involve predictive processing. Our research presents the first definite evidence for the auditory system prioritizing transitional probabilities over probabilities of individual sensory events. Forming representations for transitional probabilities paves the way for predictions of upcoming sounds. Several recent theories suggest that predictive processing provides the general basis of human perception, including important auditory functions, such as auditory scene analysis. Our

Neutrosophic Probability, Set, And Logic (first version)

OpenAIRE

Smarandache, Florentin

2000-01-01

This project is a part of a National Science Foundation interdisciplinary project proposal. Starting from a new viewpoint in philosophy, the neutrosophy, one extends the classical "probability theory", "fuzzy set" and "fuzzy logic" to , and respectively. They are useful in artificial intelligence, neural networks, evolutionary programming, neutrosophic dynamic systems, and quantum mechanics.

[Social intelligence deficits in autistic children and adolescents--subjective theories of psychosocial health care professionals].

Science.gov (United States)

Krech, M; Probst, P

1998-10-01

The paper is concerned with personal theories of health care professionals about deficiencies in social intelligence of autistic persons. In the component-model of social intelligence means the ability of individuals or groups, to interact with each other in social situations. This contains social perception, social behavior as well as social conceptions and refers to emotional, cognitive and normative aspects. 33 interviewees, working as psychologists or teachers in kindergartens, schools or therapy institutions, are questioned by a half-standardized single interview concerning their beliefs about nonverbal social abilities, social perspective taking, and construction of a theory of mind in autistic persons. The major finding is: The impairments can be found in all aspects of social intelligence. Especially emotional handicaps, which are quoted by more than 80% of the interviewees, and low cognitive preconditions of mastering social stimuli, which are quoted by nearly all interviewees, are relevant. The subjective theories of the interviewees are in accordance to the models of parents as well as the models of the leading experts. The professional relationship to autistic persons and the practical experiences of the health care professionals lead to their specific personal theories of deficiencies in social intelligence of autistic people with wide consequences in respect to the professional contact with the autistic children and young adults.

Restructuring of Values and Probabilities: Psychological Processes in Human Decision Making under Risk

International Nuclear Information System (INIS)

Svenson, Ola; Salo, Ilkka

2001-01-01

According to Differentiation and Consolidation Theory (Diff Con), the decision maker's representations of values and probabilities are interdependent and changing over time in risky decision making. This is a clear violation of most normative theories of decision making. The present contribution will present Diff Con and provide empirical illustrations of how mental representations of values and probabilities change over time. The paper concludes with a discussion of the implications of these findings concerning expert and lay people decision making about risks and hazards

A stochastic-bayesian model for the fracture probability of PWR pressure vessels

Energy Technology Data Exchange (ETDEWEB)

Francisco, Alexandre S.; Duran, Jorge Alberto R., E-mail: afrancisco@metal.eeimvr.uff.br, E-mail: duran@metal.eeimvr.uff.br [Universidade Federal Fluminense (UFF), Volta Redonda, RJ (Brazil). Dept. de Engenharia Mecanica

2013-07-01

Fracture probability of pressure vessels containing cracks can be obtained by methodologies of easy understanding, which require a deterministic treatment, complemented by statistical methods. However, more accurate results are required, methodologies need to be better formulated. This paper presents a new methodology to address this problem. First, a more rigorous methodology is obtained by means of the relationship of probability distributions that model crack incidence and nondestructive inspection efficiency using the Bayes' theorem. The result is an updated crack incidence distribution. Further, the accuracy of the methodology is improved by using a stochastic model for the crack growth. The stochastic model incorporates the statistical variability of the crack growth process, combining the stochastic theory with experimental data. Stochastic differential equations are derived by the randomization of empirical equations. From the solution of this equation, a distribution function related to the crack growth is derived. The fracture probability using both probability distribution functions is in agreement with theory, and presents realistic value for pressure vessels. (author)

A stochastic-bayesian model for the fracture probability of PWR pressure vessels

International Nuclear Information System (INIS)

Francisco, Alexandre S.; Duran, Jorge Alberto R.

2013-01-01

Fracture probability of pressure vessels containing cracks can be obtained by methodologies of easy understanding, which require a deterministic treatment, complemented by statistical methods. However, more accurate results are required, methodologies need to be better formulated. This paper presents a new methodology to address this problem. First, a more rigorous methodology is obtained by means of the relationship of probability distributions that model crack incidence and nondestructive inspection efficiency using the Bayes' theorem. The result is an updated crack incidence distribution. Further, the accuracy of the methodology is improved by using a stochastic model for the crack growth. The stochastic model incorporates the statistical variability of the crack growth process, combining the stochastic theory with experimental data. Stochastic differential equations are derived by the randomization of empirical equations. From the solution of this equation, a distribution function related to the crack growth is derived. The fracture probability using both probability distribution functions is in agreement with theory, and presents realistic value for pressure vessels. (author)

Probability theory for 3-layer remote sensing in ideal gas law environment.

Science.gov (United States)

Ben-David, Avishai; Davidson, Charles E

2013-08-26

We extend the probability model for 3-layer radiative transfer [Opt. Express 20, 10004 (2012)] to ideal gas conditions where a correlation exists between transmission and temperature of each of the 3 layers. The effect on the probability density function for the at-sensor radiances is surprisingly small, and thus the added complexity of addressing the correlation can be avoided. The small overall effect is due to (a) small perturbations by the correlation on variance population parameters and (b) cancellation of perturbation terms that appear with opposite signs in the model moment expressions.

Consistent Quantum Theory

Science.gov (United States)

Griffiths, Robert B.

2001-11-01

Quantum mechanics is one of the most fundamental yet difficult subjects in physics. Nonrelativistic quantum theory is presented here in a clear and systematic fashion, integrating Born's probabilistic interpretation with Schrödinger dynamics. Basic quantum principles are illustrated with simple examples requiring no mathematics beyond linear algebra and elementary probability theory. The quantum measurement process is consistently analyzed using fundamental quantum principles without referring to measurement. These same principles are used to resolve several of the paradoxes that have long perplexed physicists, including the double slit and Schrödinger's cat. The consistent histories formalism used here was first introduced by the author, and extended by M. Gell-Mann, J. Hartle and R. Omnès. Essential for researchers yet accessible to advanced undergraduate students in physics, chemistry, mathematics, and computer science, this book is supplementary to standard textbooks. It will also be of interest to physicists and philosophers working on the foundations of quantum mechanics. Comprehensive account Written by one of the main figures in the field Paperback edition of successful work on philosophy of quantum mechanics

On misclassication probabilities of linear and quadratic classiers ...

African Journals Online (AJOL)

We study the theoretical misclassication probability of linear and quadratic classiers and examine the performance of these classiers under distributional variations in theory and using simulation. We derive expression for Bayes errors for some competing distributions from the same family under location shift. Keywords: ...

Winter School on Operator Spaces, Noncommutative Probability and Quantum Groups

CERN Document Server

2017-01-01

Providing an introduction to current research topics in functional analysis and its applications to quantum physics, this book presents three lectures surveying recent progress and open problems.  A special focus is given to the role of symmetry in non-commutative probability, in the theory of quantum groups, and in quantum physics. The first lecture presents the close connection between distributional symmetries and independence properties. The second introduces many structures (graphs, C*-algebras, discrete groups) whose quantum symmetries are much richer than their classical symmetry groups, and describes the associated quantum symmetry groups. The last lecture shows how functional analytic and geometric ideas can be used to detect and to quantify entanglement in high dimensions.  The book will allow graduate students and young researchers to gain a better understanding of free probability, the theory of compact quantum groups, and applications of the theory of Banach spaces to quantum information. The l...

Ignition probabilities for Compact Ignition Tokamak designs

International Nuclear Information System (INIS)

Stotler, D.P.; Goldston, R.J.

1989-09-01

A global power balance code employing Monte Carlo techniques had been developed to study the ''probability of ignition'' and has been applied to several different configurations of the Compact Ignition Tokamak (CIT). Probability distributions for the critical physics parameters in the code were estimated using existing experimental data. This included a statistical evaluation of the uncertainty in extrapolating the energy confinement time. A substantial probability of ignition is predicted for CIT if peaked density profiles can be achieved or if one of the two higher plasma current configurations is employed. In other cases, values of the energy multiplication factor Q of order 10 are generally obtained. The Ignitor-U and ARIES designs are also examined briefly. Comparisons of our empirically based confinement assumptions with two theory-based transport models yield conflicting results. 41 refs., 11 figs

Python for probability, statistics, and machine learning

CERN Document Server

Unpingco, José

2016-01-01

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...

Probability as a Physical Motive

Directory of Open Access Journals (Sweden)

Peter Martin

2007-04-01

Full Text Available Recent theoretical progress in nonequilibrium thermodynamics, linking thephysical principle of Maximum Entropy Production (“MEP” to the information-theoretical“MaxEnt” principle of scientific inference, together with conjectures from theoreticalphysics that there may be no fundamental causal laws but only probabilities for physicalprocesses, and from evolutionary theory that biological systems expand “the adjacentpossible” as rapidly as possible, all lend credence to the proposition that probability shouldbe recognized as a fundamental physical motive. It is further proposed that spatial order andtemporal order are two aspects of the same thing, and that this is the essence of the secondlaw of thermodynamics.

Ramsey theory for product spaces

CERN Document Server

Dodos, Pandelis

2016-01-01

Ramsey theory is a dynamic area of combinatorics that has various applications in analysis, ergodic theory, logic, number theory, probability theory, theoretical computer science, and topological dynamics. This book is devoted to one of the most important areas of Ramsey theory-the Ramsey theory of product spaces. It is a culmination of a series of recent breakthroughs by the two authors and their students who were able to lift this theory to the infinite-dimensional case. The book presents many major results and methods in the area, such as Szemerédi's regularity method, the hypergraph removal lemma, and the density Hales-Jewett theorem. This book addresses researchers in combinatorics but also working mathematicians and advanced graduate students who are interested in Ramsey theory. The prerequisites for reading this book are rather minimal: it only requires familiarity, at the graduate level, with probability theory and real analysis. Some familiarity with the basics of Ramsey theory would be beneficial, ...

Elements of probability and statistics an introduction to probability with De Finetti’s approach and to Bayesian statistics

CERN Document Server

Biagini, Francesca

2016-01-01

This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.

An introduction to information theory

CERN Document Server

Reza, Fazlollah M

1994-01-01

Graduate-level study for engineering students presents elements of modern probability theory, information theory, coding theory, more. Emphasis on sample space, random variables, capacity, etc. Many reference tables and extensive bibliography. 1961 edition.

Restructuring of Values and Probabilities: Psychological Processes in Human Decision Making under Risk

Energy Technology Data Exchange (ETDEWEB)

Svenson, Ola; Salo, Ilkka [Stockholm Univ. (Sweden). Dept. of Psychology

2001-07-01

According to Differentiation and Consolidation Theory (Diff Con), the decision maker's representations of values and probabilities are interdependent and changing over time in risky decision making. This is a clear violation of most normative theories of decision making. The present contribution will present Diff Con and provide empirical illustrations of how mental representations of values and probabilities change over time. The paper concludes with a discussion of the implications of these findings concerning expert and lay people decision making about risks and hazards.

Introduction to the Interface of Probability and Algorithms

OpenAIRE

Aldous, David; Steele, J. Michael

1993-01-01

Probability and algorithms enjoy an almost boisterous interaction that has led to an active, extensive literature that touches fields as diverse as number theory and the design of computer hardware. This article offers a gentle introduction to the simplest, most basic ideas that underlie this development.

An analytic approach to probability tables for the unresolved resonance region

Directory of Open Access Journals (Sweden)

Brown David

2017-01-01

Full Text Available The Unresolved Resonance Region (URR connects the fast neutron region with the Resolved Resonance Region (RRR. The URR is problematic since resonances are not resolvable experimentally yet the fluctuations in the neutron cross sections play a discernible and technologically important role: the URR in a typical nucleus is in the 100 keV – 2 MeV window where the typical fission spectrum peaks. The URR also represents the transition between R-matrix theory used to described isolated resonances and Hauser-Feshbach theory which accurately describes the average cross sections. In practice, only average or systematic features of the resonances in the URR are known and are tabulated in evaluations in a nuclear data library such as ENDF/B-VII.1. Codes such as AMPX and NJOY can compute the probability distribution of the cross section in the URR under some assumptions using Monte Carlo realizations of sets of resonances. These probability distributions are stored in the so-called PURR tables. In our work, we begin to develop a scheme for computing the covariance of the cross section probability distribution analytically. Our approach offers the possibility of defining the limits of applicability of Hauser-Feshbach theory and suggests a way to calculate PURR tables directly from systematics for nuclei whose RRR is unknown, provided one makes appropriate assumptions about the shape of the cross section probability distribution.

People's Intuitions about Randomness and Probability: An Empirical Study

Science.gov (United States)

Lecoutre, Marie-Paule; Rovira, Katia; Lecoutre, Bruno; Poitevineau, Jacques

2006-01-01

What people mean by randomness should be taken into account when teaching statistical inference. This experiment explored subjective beliefs about randomness and probability through two successive tasks. Subjects were asked to categorize 16 familiar items: 8 real items from everyday life experiences, and 8 stochastic items involving a repeatable…

Local homotopy theory

CERN Document Server

Jardine, John F

2015-01-01

This monograph on the homotopy theory of topologized diagrams of spaces and spectra gives an expert account of a subject at the foundation of motivic homotopy theory and the theory of topological modular forms in stable homotopy theory. Beginning with an introduction to the homotopy theory of simplicial sets and topos theory, the book covers core topics such as the unstable homotopy theory of simplicial presheaves and sheaves, localized theories, cocycles, descent theory, non-abelian cohomology, stacks, and local stable homotopy theory. A detailed treatment of the formalism of the subject is interwoven with explanations of the motivation, development, and nuances of ideas and results. The coherence of the abstract theory is elucidated through the use of widely applicable tools, such as Barr's theorem on Boolean localization, model structures on the category of simplicial presheaves on a site, and cocycle categories. A wealth of concrete examples convey the vitality and importance of the subject in topology, n...

Probability, Statistics, and Stochastic Processes

CERN Document Server

Olofsson, Peter

2012-01-01

This book provides a unique and balanced approach to probability, statistics, and stochastic processes.   Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area.  The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and

Maximization of regional probabilities using Optimal Surface Graphs

DEFF Research Database (Denmark)

Arias Lorza, Andres M.; Van Engelen, Arna; Petersen, Jens

2018-01-01

Purpose: We present a segmentation method that maximizes regional probabilities enclosed by coupled surfaces using an Optimal Surface Graph (OSG) cut approach. This OSG cut determines the globally optimal solution given a graph constructed around an initial surface. While most methods for vessel...... wall segmentation only use edge information, we show that maximizing regional probabilities using an OSG improves the segmentation results. We applied this to automatically segment the vessel wall of the carotid artery in magnetic resonance images. Methods: First, voxel-wise regional probability maps...... were obtained using a Support Vector Machine classifier trained on local image features. Then, the OSG segments the regions which maximizes the regional probabilities considering smoothness and topological constraints. Results: The method was evaluated on 49 carotid arteries from 30 subjects...

Probability and statistics in particle physics

International Nuclear Information System (INIS)

Frodesen, A.G.; Skjeggestad, O.

1979-01-01

Probability theory is entered into at an elementary level and given a simple and detailed exposition. The material on statistics has been organised with an eye to the experimental physicist's practical need, which is likely to be statistical methods for estimation or decision-making. The book is intended for graduate students and research workers in experimental high energy and elementary particle physics, and numerous examples from these fields are presented. (JIW)

Individual variation in social aggression and the probability of inheritance: theory and a field test.

Science.gov (United States)

Cant, Michael A; Llop, Justine B; Field, Jeremy

2006-06-01

Recent theory suggests that much of the wide variation in individual behavior that exists within cooperative animal societies can be explained by variation in the future direct component of fitness, or the probability of inheritance. Here we develop two models to explore the effect of variation in future fitness on social aggression. The models predict that rates of aggression will be highest toward the front of the queue to inherit and will be higher in larger, more productive groups. A third prediction is that, in seasonal animals, aggression will increase as the time available to inherit the breeding position runs out. We tested these predictions using a model social species, the paper wasp Polistes dominulus. We found that rates of both aggressive "displays" (aimed at individuals of lower rank) and aggressive "tests" (aimed at individuals of higher rank) decreased down the hierarchy, as predicted by our models. The only other significant factor affecting aggression rates was date, with more aggression observed later in the season, also as predicted. Variation in future fitness due to inheritance rank is the hidden factor accounting for much of the variation in aggressiveness among apparently equivalent individuals in this species.

Introduction to probability with statistical applications

CERN Document Server

Schay, Géza

2016-01-01

Now in its second edition, this textbook serves as an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. More classical examples such as Montmort's problem, the ballot problem, and Bertrand’s paradox are now included, along with applications such as the Maxwell-Boltzmann and Bose-Einstein distributions in physics. Key features in new edition: * 35 new exercises * Expanded section on the algebra of sets * Expanded chapters on probabilities to include more classical examples * New section on regression * Online instructors' manual containing solutions to all exercises

Generalized Galilean transformations and the measurement problem in the entropic dynamics approach to quantum theory

Science.gov (United States)

Johnson, David T.

Quantum mechanics is an extremely successful and accurate physical theory, yet since its inception, it has been afflicted with numerous conceptual difficulties. The primary subject of this thesis is the theory of entropic quantum dynamics (EQD), which seeks to avoid these conceptual problems by interpreting quantum theory from an informational perspective. We begin by reviewing Cox's work in describing probability theory as a means of rationally and consistently quantifying uncertainties. We then discuss how probabilities can be updated according to either Bayes' theorem or the extended method of maximum entropy (ME). After that discussion, we review the work of Caticha and Giffin that shows that Bayes' theorem is a special case of ME. This important result demonstrates that the ME method is the general method for updating probabilities. We then review some motivating difficulties in quantum mechanics before discussing Caticha's work in deriving quantum theory from the approach of entropic dynamics, which concludes our review. After entropic dynamics is introduced, we develop the concepts of symmetries and transformations from an informational perspective. The primary result is the formulation of a symmetry condition that any transformation must satisfy in order to qualify as a symmetry in EQD. We then proceed to apply this condition to the extended Galilean transformation. This transformation is of interest as it exhibits features of both special and general relativity. The transformation yields a gravitational potential that arises from an equivalence of information. We conclude the thesis with a discussion of the measurement problem in quantum mechanics. We discuss the difficulties that arise in the standard quantum mechanical approach to measurement before developing our theory of entropic measurement. In entropic dynamics, position is the only observable. We show how a theory built on this one observable can account for the multitude of measurements present in

Hybrid Processing of Measurable and Subjective Data; TOPICAL

International Nuclear Information System (INIS)

COOPER, J. ARLIN; ROGINSKI, ROBERT J.

2001-01-01

Conventional systems surety analysis is basically restricted to measurable or physical-model-derived data. However, most analyses, including high-consequence system surety analysis, must also utilize subjective information. In order to address this need, there has been considerable effort on analytically incorporating engineering judgment. For example, Dempster-Shafer theory establishes a framework in which frequentist probability and Bayesian incorporation of new data are subsets. Although Bayesian and Dempster-Shafer methodology both allow judgment, neither derives results that can indicate the relative amounts of subjective judgment and measurable data in the results. The methodology described in this report addresses these problems through a hybrid-mathematics-based process that allows tracking of the degree of subjective information in the output, thereby providing more informative (as well as more appropriate) results. In addition, most high consequence systems offer difficult-to-analyze situations. For example, in the Sandia National Laboratories nuclear weapons program, the probability that a weapon responds safely when exposed to an abnormal environment (e.g., lightning, crush, metal-melting temperatures) must be assured to meet a specific requirement. There are also non-probabilistic DOE and DoD requirements (e.g., for determining the adequacy of positive measures). The type of processing required for these and similar situations transcends conventional probabilistic and human factors methodology. The results described herein address these situations by efficiently utilizing subjective and objective information in a hybrid mathematical structure in order to directly apply to the surety assessment of high consequence systems. The results can also improve the quality of the information currently provided to decision-makers. To this end, objective inputs are processed in a conventional manner; while subjective inputs are derived from the combined engineering

Efficient elicitation of utility and probability weighting functions

Czech Academy of Sciences Publication Activity Database

Blavatskyy, Pavlo R.

-, č. 211 (2004), s. 1-31 ISSN 1424-0459 Institutional research plan: CEZ:AV0Z7085904 Keywords : decision theory * rank-dependent expected utility * cumulative prospect theory Subject RIV: AH - Economics http://www.iew.unizh.ch/wp/iewwp211.pdf

Some applications of the fractional Poisson probability distribution

International Nuclear Information System (INIS)

Laskin, Nick

2009-01-01

Physical and mathematical applications of the recently invented fractional Poisson probability distribution have been presented. As a physical application, a new family of quantum coherent states has been introduced and studied. As mathematical applications, we have developed the fractional generalization of Bell polynomials, Bell numbers, and Stirling numbers of the second kind. The appearance of fractional Bell polynomials is natural if one evaluates the diagonal matrix element of the evolution operator in the basis of newly introduced quantum coherent states. Fractional Stirling numbers of the second kind have been introduced and applied to evaluate the skewness and kurtosis of the fractional Poisson probability distribution function. A representation of the Bernoulli numbers in terms of fractional Stirling numbers of the second kind has been found. In the limit case when the fractional Poisson probability distribution becomes the Poisson probability distribution, all of the above listed developments and implementations turn into the well-known results of the quantum optics and the theory of combinatorial numbers.

Generalized Probability-Probability Plots

NARCIS (Netherlands)

Mushkudiani, N.A.; Einmahl, J.H.J.

2004-01-01

We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data.These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical P-P

INTRODUCTION IN TECHNOLOGY CONCEPTUALIZATION THE SUBJECT DOMAIN OF SOCIOLOGY: EXPANSION OF THE THEORY (in the example of relationship/kinship

Directory of Open Access Journals (Sweden)

A. Yu. Ivanov

2017-01-01

Full Text Available Presented article is the second of two articles, the aim of which is to introduce the reader has no special mathematical training, with the possibilities of application of mathematical methods developed in the scientific direction of “Conceptual analysis and design of systems of organizational management (CAD SOM”, designed to solve a variety of tasks, such as technical and humanitarian spheres on the basis of the proposed methodological approach to the mathematization of the theoretical knowledge. At the heart of this methodological approach is a process of conceptualization, which is understood as a theoretical study of qualitative aspects of a selected domain using mathematical forms (axiomatic theory, the locking connection between the concepts of logical derivability characterizing this subject area. Designed axiomatic theory – conceptual scheme – is the basis for building database structures, decision-making processes, a variety of phenomena subject area, structure and genesis of domain analysis and other tasks. One of the main advantages of the sending of methodological approach is the ability to work with complex regions based on the controlled synthesis tool terminal theory of conceptual schemes, explicated simple fragments of the subject area. Given the non-mathematical preparation of the reader, the contents of the methods illustrated by conceptualizing a conceptually simple subject areas – areas related relations, as well as the choice of one of the most simple goals conceptualization – structuring the domain and build a variety of its phenomena. The first article was given a brief description of mathematical methods, describes the main stages of the conceptualization of the subject areas, ranging from the definition of the boundaries of the domain and ending with the theory of the synthesis of the terminal and determine its compliance with the tasks of conceptualizing. In the chosen example – areas related relations �

Estimation of Extreme Response and Failure Probability of Wind Turbines under Normal Operation using Probability Density Evolution Method

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Nielsen, Søren R.K.; Liu, W. F.

2013-01-01

Estimation of extreme response and failure probability of structures subjected to ultimate design loads is essential for structural design of wind turbines according to the new standard IEC61400-1. This task is focused on in the present paper in virtue of probability density evolution method (PDEM......), which underlies the schemes of random vibration analysis and structural reliability assessment. The short-term rare failure probability of 5-mega-watt wind turbines, for illustrative purposes, in case of given mean wind speeds and turbulence levels is investigated through the scheme of extreme value...... distribution instead of any other approximate schemes of fitted distribution currently used in statistical extrapolation techniques. Besides, the comparative studies against the classical fitted distributions and the standard Monte Carlo techniques are carried out. Numerical results indicate that PDEM exhibits...

Probability Aggregates in Probability Answer Set Programming

OpenAIRE

Saad, Emad

2013-01-01

Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...

Towards a definition of SUBJECT in binding domains and subject ...

African Journals Online (AJOL)

be antecedents for subject-oriented anaphors (e.g. Maling 1984) ... 1985), it is unclear what actually determines this binding behaviour, or why subjects should ..... contexts can be unified by the fact that both functionally determine their complements. ...... Binding theory, control and pro. ... San Diego: Academic Press. pp. 179 ...

Grammaticality, Acceptability, and Probability: A Probabilistic View of Linguistic Knowledge.

Science.gov (United States)

Lau, Jey Han; Clark, Alexander; Lappin, Shalom

2017-07-01

The question of whether humans represent grammatical knowledge as a binary condition on membership in a set of well-formed sentences, or as a probabilistic property has been the subject of debate among linguists, psychologists, and cognitive scientists for many decades. Acceptability judgments present a serious problem for both classical binary and probabilistic theories of grammaticality. These judgements are gradient in nature, and so cannot be directly accommodated in a binary formal grammar. However, it is also not possible to simply reduce acceptability to probability. The acceptability of a sentence is not the same as the likelihood of its occurrence, which is, in part, determined by factors like sentence length and lexical frequency. In this paper, we present the results of a set of large-scale experiments using crowd-sourced acceptability judgments that demonstrate gradience to be a pervasive feature in acceptability judgments. We then show how one can predict acceptability judgments on the basis of probability by augmenting probabilistic language models with an acceptability measure. This is a function that normalizes probability values to eliminate the confounding factors of length and lexical frequency. We describe a sequence of modeling experiments with unsupervised language models drawn from state-of-the-art machine learning methods in natural language processing. Several of these models achieve very encouraging levels of accuracy in the acceptability prediction task, as measured by the correlation between the acceptability measure scores and mean human acceptability values. We consider the relevance of these results to the debate on the nature of grammatical competence, and we argue that they support the view that linguistic knowledge can be intrinsically probabilistic. Copyright © 2016 Cognitive Science Society, Inc.

The control processes and subjective well-being of Chinese teachers: Evidence of convergence with and divergence from the key propositions of the motivational theory of life-span development

Directory of Open Access Journals (Sweden)

Wan-Chi eWong

2014-05-01

Full Text Available An analytical review of the motivational theory of life-span development reveals that this theory has undergone a series of elegant theoretical integrations. Its claim to universality nonetheless brings forth unresolved controversies. With the purpose of scrutinizing the key propositions of this theory, an empirical study was designed to examine the control processes and subjective well-being of Chinese teachers (N = 637. The OPS-Scales (Optimization in Primary and Secondary Control Scales for the Domain of Teaching were constructed to assess patterns of control processes. Three facets of subjective well-being were investigated with the Positive and Negative Affect Schedule, the Life Satisfaction Scale, and the Subjective Vitality Scale. The results revealed certain aspects of alignment with and certain divergences from the key propositions of the motivational theory of life-span development. Neither primacy of primary control nor primacy of secondary control was clearly supported. Notably, using different criteria for subjective well-being yielded different subtypes of primary and secondary control as predictors. The hypothesized life-span trajectories of primary and secondary control received limited support. To advance the theory in this area, we recommend incorporating Lakatos’ ideas about sophisticated falsification by specifying the hard core of the motivational theory of life-span development and articulating new auxiliary hypotheses.

Decreased Serum Lipids in Patients with Probable Alzheimer´s Disease

Directory of Open Access Journals (Sweden)

Orhan Lepara

2009-08-01

Full Text Available Alzheimer’s disease (AD is a multifactorial disease but its aetiology and pathophisiology are still not fully understood. Epidemiologic studies examining the association between lipids and dementia have reported conflicting results. High total cholesterol has been associated with both an increased, and decreased, risk of AD and/or vascular dementia (VAD, whereas other studies found no association. The aim of this study was to investigate the serum lipids concentration in patients with probable AD, as well as possible correlation between serum lipids concentrations and cognitive impairment.Our cross-sectional study included 30 patients with probable AD and 30 age and sex matched control subjects. The probable AD was clinically diagnosed by NINCDS-ADRDA criteria. Serum total cholesterol (TC, high-density lipoprotein cholesterol (HDL-C and triglyceride (TG levels were determined at the initial assessment using standard enzymatic colorimetric techniques. Low-den- sity lipoprotein cholesterol (LDL-C and very low density lipoprotein cholesterol (VLDL-C levels were calculated. Subjects with probable AD had significantly lower serum TG (p<0,01, TC (p<0,05, LDL-C (p<0,05 and VLDL-C (p<0,01 compared to the control group. We did not observe signifi-cant difference in HDL-C level between patients with probable AD and control subjects. Negative, although not significant correlation between TG, TC and VLDL-C and MMSE in patients with AD was observed. In the control group of subjects there was a negative correlation between TC and MMSE but it was not statistically significant (r = -0,28. Further studies are required to explore the possibility for serum lipids to serve as diagnostic and therapeutic markers of AD.

Quantum probability and cognitive modeling: some cautions and a promising direction in modeling physics learning.

Science.gov (United States)

Franceschetti, Donald R; Gire, Elizabeth

2013-06-01

Quantum probability theory offers a viable alternative to classical probability, although there are some ambiguities inherent in transferring the quantum formalism to a less determined realm. A number of physicists are now looking at the applicability of quantum ideas to the assessment of physics learning, an area particularly suited to quantum probability ideas.

Risk-taking in disorders of natural and drug rewards: neural correlates and effects of probability, valence, and magnitude.

Science.gov (United States)

Voon, Valerie; Morris, Laurel S; Irvine, Michael A; Ruck, Christian; Worbe, Yulia; Derbyshire, Katherine; Rankov, Vladan; Schreiber, Liana Rn; Odlaug, Brian L; Harrison, Neil A; Wood, Jonathan; Robbins, Trevor W; Bullmore, Edward T; Grant, Jon E

2015-03-01

Pathological behaviors toward drugs and food rewards have underlying commonalities. Risk-taking has a fourfold pattern varying as a function of probability and valence leading to the nonlinearity of probability weighting with overweighting of small probabilities and underweighting of large probabilities. Here we assess these influences on risk-taking in patients with pathological behaviors toward drug and food rewards and examine structural neural correlates of nonlinearity of probability weighting in healthy volunteers. In the anticipation of rewards, subjects with binge eating disorder show greater risk-taking, similar to substance-use disorders. Methamphetamine-dependent subjects had greater nonlinearity of probability weighting along with impaired subjective discrimination of probability and reward magnitude. Ex-smokers also had lower risk-taking to rewards compared with non-smokers. In the anticipation of losses, obesity without binge eating had a similar pattern to other substance-use disorders. Obese subjects with binge eating also have impaired discrimination of subjective value similar to that of the methamphetamine-dependent subjects. Nonlinearity of probability weighting was associated with lower gray matter volume in dorsolateral and ventromedial prefrontal cortex and orbitofrontal cortex in healthy volunteers. Our findings support a distinct subtype of binge eating disorder in obesity with similarities in risk-taking in the reward domain to substance use disorders. The results dovetail with the current approach of defining mechanistically based dimensional approaches rather than categorical approaches to psychiatric disorders. The relationship to risk probability and valence may underlie the propensity toward pathological behaviors toward different types of rewards.

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

Science.gov (United States)

Gloger, Oliver; Tönnies, Klaus; Mensel, Birger; Völzke, Henry

2015-11-01

In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches.

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data

International Nuclear Information System (INIS)

Gloger, Oliver; Völzke, Henry; Tönnies, Klaus; Mensel, Birger

2015-01-01

In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Especially in large-scale population-based studies organ volumetry is highly relevant requiring exact organ segmentation. Since manual segmentation is time-consuming and prone to reader variability, large-scale studies need automatized methods to perform organ segmentation. Fully automatic organ segmentation in native MR image data has proven to be a very challenging task. Imaging artifacts as well as inter- and intrasubject MR-intensity differences complicate the application of supervised learning strategies. Thus, we propose a modularized framework of a two-stepped probabilistic approach that generates subject-specific probability maps for renal parenchyma tissue, which are refined subsequently by using several, extended segmentation strategies. We present a three class-based support vector machine recognition system that incorporates Fourier descriptors as shape features to recognize and segment characteristic parenchyma parts. Probabilistic methods use the segmented characteristic parenchyma parts to generate high quality subject-specific parenchyma probability maps. Several refinement strategies including a final shape-based 3D level set segmentation technique are used in subsequent processing modules to segment renal parenchyma. Furthermore, our framework recognizes and excludes renal cysts from parenchymal volume, which is important to analyze renal functions. Volume errors and Dice coefficients show that our presented framework outperforms existing approaches. (paper)

Commutative monads as a theory of distributions

DEFF Research Database (Denmark)

Kock, Anders

2012-01-01

It is shown how the theory of commutative monads provides an axiomatic framework for several aspects of distribution theory in a broad sense, including probability distributions, physical extensive quantities, and Schwartz distributions of compact support. Among the particular aspects considered...... here are the notions of convolution, density, expectation, and conditional probability....

Foreword [International conference on algebra, analysis and quantum probability

International Nuclear Information System (INIS)

2016-01-01

The present volume of the Journal of Physics: Conference Series represents contributions from participants of the International Conference ’’Algebra, Analysis and Quantum Probability” (Tashkent, 10-12 September 2015) organized by the Institute of Mathematics and the Faculty of Mechanics and Mathematics of the National University of Uzbekistan (NUUz) in collaboration with University Putra Malaysia (UPM) and International Islamic University Malaysia (IIUM). The Conference is dedicated to the 100th anniversary of one of the outstanding scientists of Uzbekistan, the founder of the Tashkent scientific school of functional analysis, who has initiated the investigations on operator algebras and quantum probability theory in Uzbekistan - Professor Tashmukhamed Alievich Sarymsakov (10 Sept. 1915 - 19 Dec. 1995). Among the mathematical community Professor T. A. Sarymsakov is widely known for his research in the fields of probability theory, functional analysis, general topology and their applications. A gifted teacher and skilful organizer he had a beneficial effect on the development of many new mathematicians in Uzbekistan. Professor T.A. Sarymsakov, an outstanding organizer of science in Uzbekistan, was one of the founders of the Uzbekistan Academy of Sciences, where from 1943 he was a member and Vice President, and from 1946 to 1952 president of the Academy of Sciences. Professor Sarymsakov successfully combined his fruitful scientific research with teaching and social work. During 1943-1944, 1952-1958 and 1971-1983 he was the rector of Tashkent State University (now the National University of Uzbekistan). He has made a significant contribution to the development of higher education in Uzbekistan, serving from 1959 to 1960 as the Chairman of the State Committee, and from 1960 to 1971 as the Minister of Higher and Secondary Special Education of Uzbekistan. The main objective of the scientific conference was to facilitate communication and collaboration between

How Can Histograms Be Useful for Introducing Continuous Probability Distributions?

Science.gov (United States)

Derouet, Charlotte; Parzysz, Bernard

2016-01-01

The teaching of probability has changed a great deal since the end of the last century. The development of technologies is indeed part of this evolution. In France, continuous probability distributions began to be studied in 2002 by scientific 12th graders, but this subject was marginal and appeared only as an application of integral calculus.…

Single, Complete, Probability Spaces Consistent With EPR-Bohm-Bell Experimental Data

Science.gov (United States)

Avis, David; Fischer, Paul; Hilbert, Astrid; Khrennikov, Andrei

2009-03-01

We show that paradoxical consequences of violations of Bell's inequality are induced by the use of an unsuitable probabilistic description for the EPR-Bohm-Bell experiment. The conventional description (due to Bell) is based on a combination of statistical data collected for different settings of polarization beam splitters (PBSs). In fact, such data consists of some conditional probabilities which only partially define a probability space. Ignoring this conditioning leads to apparent contradictions in the classical probabilistic model (due to Kolmogorov). We show how to make a completely consistent probabilistic model by taking into account the probabilities of selecting the settings of the PBSs. Our model matches both the experimental data and is consistent with classical probability theory.

Quantum Decision Theory in Simple Risky Choices

Science.gov (United States)

Favre, Maroussia; Wittwer, Amrei; Heinimann, Hans Rudolf; Yukalov, Vyacheslav I.; Sornette, Didier

2016-01-01

Quantum decision theory (QDT) is a recently developed theory of decision making based on the mathematics of Hilbert spaces, a framework known in physics for its application to quantum mechanics. This framework formalizes the concept of uncertainty and other effects that are particularly manifest in cognitive processes, which makes it well suited for the study of decision making. QDT describes a decision maker’s choice as a stochastic event occurring with a probability that is the sum of an objective utility factor and a subjective attraction factor. QDT offers a prediction for the average effect of subjectivity on decision makers, the quarter law. We examine individual and aggregated (group) data, and find that the results are in good agreement with the quarter law at the level of groups. At the individual level, it appears that the quarter law could be refined in order to reflect individual characteristics. This article revisits the formalism of QDT along a concrete example and offers a practical guide to researchers who are interested in applying QDT to a dataset of binary lotteries in the domain of gains. PMID:27936217

Wigner function and the probability representation of quantum states

Directory of Open Access Journals (Sweden)

Man’ko Margarita A.

2014-01-01

Full Text Available The relation of theWigner function with the fair probability distribution called tomographic distribution or quantum tomogram associated with the quantum state is reviewed. The connection of the tomographic picture of quantum mechanics with the integral Radon transform of the Wigner quasidistribution is discussed. The Wigner–Moyal equation for the Wigner function is presented in the form of kinetic equation for the tomographic probability distribution both in quantum mechanics and in the classical limit of the Liouville equation. The calculation of moments of physical observables in terms of integrals with the state tomographic probability distributions is constructed having a standard form of averaging in the probability theory. New uncertainty relations for the position and momentum are written in terms of optical tomograms suitable for directexperimental check. Some recent experiments on checking the uncertainty relations including the entropic uncertainty relations are discussed.

Probability approaching method (PAM) and its application on fuel management optimization

International Nuclear Information System (INIS)

Liu, Z.; Hu, Y.; Shi, G.

2004-01-01

For multi-cycle reloading optimization problem, a new solving scheme is presented. The multi-cycle problem is de-coupled into a number of relatively independent mono-cycle issues, then this non-linear programming problem with complex constraints is solved by an advanced new algorithm -probability approaching method (PAM), which is based on probability theory. The result on simplified core model shows well effect of this new multi-cycle optimization scheme. (authors)

Decision-making in probability and statistics Chilean curriculum

DEFF Research Database (Denmark)

Elicer, Raimundo

2018-01-01

Probability and statistics have become prominent subjects in school mathematics curricula. As an exemplary case, I investigate the role of decision making in the justification for probability and statistics in the current Chilean upper secondary mathematics curriculum. For addressing this concern......, I draw upon Fairclough’s model for Critical Discourse Analysis to analyse selected texts as examples of discourse practices. The texts are interconnected with politically driven ideas of stochastics “for all”, the notion of statistical literacy coined by statisticians’ communities, schooling...

High throughput nonparametric probability density estimation.

Science.gov (United States)

Farmer, Jenny; Jacobs, Donald

2018-01-01

In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.

Probability of detection of clinical seizures using heart rate changes.

Science.gov (United States)

Osorio, Ivan; Manly, B F J

2015-08-01

Heart rate-based seizure detection is a viable complement or alternative to ECoG/EEG. This study investigates the role of various biological factors on the probability of clinical seizure detection using heart rate. Regression models were applied to 266 clinical seizures recorded from 72 subjects to investigate if factors such as age, gender, years with epilepsy, etiology, seizure site origin, seizure class, and data collection centers, among others, shape the probability of EKG-based seizure detection. Clinical seizure detection probability based on heart rate changes, is significantly (pprobability of detecting clinical seizures (>0.8 in the majority of subjects) using heart rate is highest for complex partial seizures, increases with a patient's years with epilepsy, is lower for females than for males and is unrelated to the side of hemisphere origin. Clinical seizure detection probability using heart rate is multi-factorially dependent and sufficiently high (>0.8) in most cases to be clinically useful. Knowledge of the role that these factors play in shaping said probability will enhance its applicability and usefulness. Heart rate is a reliable and practical signal for extra-cerebral detection of clinical seizures originating from or spreading to central autonomic network structures. Copyright © 2015 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Probability Weighting as Evolutionary Second-best

OpenAIRE

Herold, Florian; Netzer, Nick

2011-01-01

The economic concept of the second-best involves the idea that multiple simultaneous deviations from a hypothetical first-best optimum may be optimal once the first-best itself can no longer be achieved, since one distortion may partially compensate for another. Within an evolutionary framework, we translate this concept to behavior under uncertainty. We argue that the two main components of prospect theory, the value function and the probability weighting function, are complements in the sec...

Quantum probability, choice in large worlds, and the statistical structure of reality.

Science.gov (United States)

Ross, Don; Ladyman, James

2013-06-01

Classical probability models of incentive response are inadequate in "large worlds," where the dimensions of relative risk and the dimensions of similarity in outcome comparisons typically differ. Quantum probability models for choice in large worlds may be motivated pragmatically - there is no third theory - or metaphysically: statistical processing in the brain adapts to the true scale-relative structure of the universe.

A transmission probability method for calculation of neutron flux distributions in hexagonal geometry

International Nuclear Information System (INIS)

Wasastjerna, F.; Lux, I.

1980-03-01

A transmission probability method implemented in the program TPHEX is described. This program was developed for the calculation of neutron flux distributions in hexagonal light water reactor fuel assemblies. The accuracy appears to be superior to diffusion theory, and the computation time is shorter than that of the collision probability method. (author)

Strong lensing probability in TeVeS (tensor-vector-scalar) theory

Science.gov (United States)

Chen, Da-Ming

2008-01-01

We recalculate the strong lensing probability as a function of the image separation in TeVeS (tensor-vector-scalar) cosmology, which is a relativistic version of MOND (MOdified Newtonian Dynamics). The lens is modeled by the Hernquist profile. We assume an open cosmology with Ωb = 0.04 and ΩΛ = 0.5 and three different kinds of interpolating functions. Two different galaxy stellar mass functions (GSMF) are adopted: PHJ (Panter, Heavens and Jimenez 2004 Mon. Not. R. Astron. Soc. 355 764) determined from SDSS data release 1 and Fontana (Fontana et al 2006 Astron. Astrophys. 459 745) from GOODS-MUSIC catalog. We compare our results with both the predicted probabilities for lenses from singular isothermal sphere galaxy halos in LCDM (Lambda cold dark matter) with a Schechter-fit velocity function, and the observational results for the well defined combined sample of the Cosmic Lens All-Sky Survey (CLASS) and Jodrell Bank/Very Large Array Astrometric Survey (JVAS). It turns out that the interpolating function μ(x) = x/(1+x) combined with Fontana GSMF matches the results from CLASS/JVAS quite well.

Rejecting probability summation for radial frequency patterns, not so Quick!

Science.gov (United States)

Baldwin, Alex S; Schmidtmann, Gunnar; Kingdom, Frederick A A; Hess, Robert F

2016-05-01

Radial frequency (RF) patterns are used to assess how the visual system processes shape. They are thought to be detected globally. This is supported by studies that have found summation for RF patterns to be greater than what is possible if the parts were being independently detected and performance only then improved with an increasing number of cycles by probability summation between them. However, the model of probability summation employed in these previous studies was based on High Threshold Theory (HTT), rather than Signal Detection Theory (SDT). We conducted rating scale experiments to investigate the receiver operating characteristics. We find these are of the curved form predicted by SDT, rather than the straight lines predicted by HTT. This means that to test probability summation we must use a model based on SDT. We conducted a set of summation experiments finding that thresholds decrease as the number of modulated cycles increases at approximately the same rate as previously found. As this could be consistent with either additive or probability summation, we performed maximum-likelihood fitting of a set of summation models (Matlab code provided in our Supplementary material) and assessed the fits using cross validation. We find we are not able to distinguish whether the responses to the parts of an RF pattern are combined by additive or probability summation, because the predictions are too similar. We present similar results for summation between separate RF patterns, suggesting that the summation process there may be the same as that within a single RF. Copyright © 2016 Elsevier Ltd. All rights reserved.

Measures, Probability and Holography in Cosmology

Science.gov (United States)

Phillips, Daniel

This dissertation compiles four research projects on predicting values for cosmological parameters and models of the universe on the broadest scale. The first examines the Causal Entropic Principle (CEP) in inhomogeneous cosmologies. The CEP aims to predict the unexpectedly small value of the cosmological constant Lambda using a weighting by entropy increase on causal diamonds. The original work assumed a purely isotropic and homogeneous cosmology. But even the level of inhomogeneity observed in our universe forces reconsideration of certain arguments about entropy production. In particular, we must consider an ensemble of causal diamonds associated with each background cosmology and we can no longer immediately discard entropy production in the far future of the universe. Depending on our choices for a probability measure and our treatment of black hole evaporation, the prediction for Lambda may be left intact or dramatically altered. The second related project extends the CEP to universes with curvature. We have found that curvature values larger than rho k = 40rhom are disfavored by more than $99.99% and a peak value at rhoLambda = 7.9 x 10-123 and rhok =4.3rho m for open universes. For universes that allow only positive curvature or both positive and negative curvature, we find a correlation between curvature and dark energy that leads to an extended region of preferred values. Our universe is found to be disfavored to an extent depending the priors on curvature. We also provide a comparison to previous anthropic constraints on open universes and discuss future directions for this work. The third project examines how cosmologists should formulate basic questions of probability. We argue using simple models that all successful practical uses of probabilities originate in quantum fluctuations in the microscopic physical world around us, often propagated to macroscopic scales. Thus we claim there is no physically verified fully classical theory of probability. We

Emptiness formation probability and quantum Knizhnik-Zamolodchikov equation

International Nuclear Information System (INIS)

Boos, H.E.; Korepin, V.E.; Smirnov, F.A.

2003-01-01

We consider the one-dimensional XXX spin-1/2 Heisenberg antiferromagnet at zero temperature and zero magnetic field. We are interested in a probability of formation of a ferromagnetic string P(n) in the antiferromagnetic ground-state. We call it emptiness formation probability (EFP). We suggest a new technique for computation of the EFP in the inhomogeneous case. It is based on the quantum Knizhnik-Zamolodchikov equation (qKZ). We calculate EFP for n≤6 for inhomogeneous case. The homogeneous limit confirms our hypothesis about the relation of quantum correlations and number theory. We also make a conjecture about a structure of EFP for arbitrary n

Expert Opinion Elicitation Using Fuzzy Set Theory and Distempers-Shaker's Theory

International Nuclear Information System (INIS)

Yu, Donghan

1993-01-01

This study presents a new approach for expert opinion elicitation. The need to work with rare events and limited data is severe accident have led analysts to use expert opinions extensively. Unlike the conventional approaches using point-valued probabilities, the study proposes the concept of fuzzy probability to represent expert opinion. The use of fuzzy probability has an advantage over the conventional approach when an expert's judgment is used under limited data and imprecise knowledge. The study demonstrates a method of combining fuzzy probabilities in a manner consistent with the Distempers-Shaper's Theory (DDT). The propagation of fuzzy probabilities through a system is also introduced

Probability and containment of turbine missiles

International Nuclear Information System (INIS)

Yeh, G.C.K.

1976-01-01

With the trend toward ever larger power generating plants with large high-speed turbines, an important plant design consideration is the potential for and consequences of mechanical failure of turbine rotors. Such rotor failure could result in high-velocity disc fragments (turbine missiles) perforating the turbine casing and jeopardizing vital plant systems. The designer must first estimate the probability of any turbine missile damaging any safety-related plant component for his turbine and his plant arrangement. If the probability is not low enough to be acceptable to the regulatory agency, he must design a shield to contain the postulated turbine missiles. Alternatively, the shield could be designed to retard (to reduce the velocity of) the missiles such that they would not damage any vital plant system. In this paper, some of the presently available references that can be used to evaluate the probability, containment and retardation of turbine missiles are reviewed; various alternative methods are compared; and subjects for future research are recommended. (Auth.)

Continuation of probability density functions using a generalized Lyapunov approach

NARCIS (Netherlands)

Baars, S.; Viebahn, J. P.; Mulder, T. E.; Kuehn, C.; Wubs, F. W.; Dijkstra, H. A.

2017-01-01

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial

Fractal supersymmetric QM, Geometric Probability and the Riemann Hypothesis

CERN Document Server

Castro, C

2004-01-01

The Riemann's hypothesis (RH) states that the nontrivial zeros of the Riemann zeta-function are of the form $ s_n =1/2+i\\lambda_n $. Earlier work on the RH based on supersymmetric QM, whose potential was related to the Gauss-Jacobi theta series, allows to provide the proper framework to construct the well defined algorithm to compute the probability to find a zero (an infinity of zeros) in the critical line. Geometric probability theory furnishes the answer to the very difficult question whether the probability that the RH is true is indeed equal to unity or not. To test the validity of this geometric probabilistic framework to compute the probability if the RH is true, we apply it directly to the the hyperbolic sine function $ \\sinh (s) $ case which obeys a trivial analog of the RH (the HSRH). Its zeros are equally spaced in the imaginary axis $ s_n = 0 + i n \\pi $. The geometric probability to find a zero (and an infinity of zeros) in the imaginary axis is exactly unity. We proceed with a fractal supersymme...

Quantum-correlation breaking channels, quantum conditional probability and Perron-Frobenius theory

Science.gov (United States)

Chruściński, Dariusz

2013-03-01

Using the quantum analog of conditional probability and classical Bayes theorem we discuss some aspects of particular entanglement breaking channels: quantum-classical and classical-classical channels. Applying the quantum analog of Perron-Frobenius theorem we generalize the recent result of Korbicz et al. (2012) [8] on full and spectrum broadcasting from quantum-classical channels to arbitrary quantum channels.

Quantum-correlation breaking channels, quantum conditional probability and Perron–Frobenius theory

International Nuclear Information System (INIS)

Chruściński, Dariusz

2013-01-01

Using the quantum analog of conditional probability and classical Bayes theorem we discuss some aspects of particular entanglement breaking channels: quantum–classical and classical–classical channels. Applying the quantum analog of Perron–Frobenius theorem we generalize the recent result of Korbicz et al. (2012) [8] on full and spectrum broadcasting from quantum–classical channels to arbitrary quantum channels.

Negative probability in the framework of combined probability

OpenAIRE

Burgin, Mark

2013-01-01

Negative probability has found diverse applications in theoretical physics. Thus, construction of sound and rigorous mathematical foundations for negative probability is important for physics. There are different axiomatizations of conventional probability. So, it is natural that negative probability also has different axiomatic frameworks. In the previous publications (Burgin, 2009; 2010), negative probability was mathematically formalized and rigorously interpreted in the context of extende...

The role of stop-signal probability and expectation in proactive inhibition

NARCIS (Netherlands)

Vink, Matthijs; Kaldewaij, Reinoud; Zandbelt, Bram B; Pas, Pascal; du Plessis, Stefan

The subjective belief of what will happen plays an important role across many cognitive domains, including response inhibition. However, tasks that study inhibition do not distinguish between the processing of objective contextual cues indicating stop-signal probability and the subjective

Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer's disease

International Nuclear Information System (INIS)

Arlt, Soenke; Jahn, Holger; Eichenlaub, Martin; Brassen, Stefanie; Wilke, Florian; Apostolova, Ivayla; Buchert, Ralph; Wenzel, Fabian; Young, Stewart; Thiele, Frank

2009-01-01

Brain imaging of FDG uptake and cerebrospinal fluid (CSF) concentration of amyloid-beta 1-42 (Aβ 1-42 ) or tau proteins are promising biomarkers in the diagnosis of Alzheimer's disease (AD). There is still uncertainty regarding any association between decreased FDG uptake and alterations in CSF markers. The relationship between FDG uptake, CSF Aβ 1-42 and total tau (T-tau), as well as the Mini-Mental State Examination (MMSE) score was investigated in 34 subjects with probable AD using step-wise linear regression. FDG uptake was scaled to the pons. Scaled FDG uptake was significantly reduced in the probable AD subjects compared to 17 controls bilaterally in the precuneus/posterior cingulate area, angular gyrus/inferior parietal cortex, inferior temporal/midtemporal cortex, midfrontal cortex, and left caudate. Voxel-based single-subject analysis of the probable AD subjects at p 1-42 . Scaled FDG uptake in the caudate was positively correlated with CSF T-tau. The extent and local severity of the reduction in FDG uptake in probable AD subjects are associated with cognitive impairment. In addition, there appears to be a relationship between local FDG uptake and CSF biomarkers which differs between different brain regions. (orig.)

analysis of the probability of channel satisfactory state in p2p live

African Journals Online (AJOL)

userpc

churn and bits flow was modelled as fluid flow. The applicability of the theory of probability was deduced from Kelly (1991). Section II of the paper provides the model of. P2P live streaming systems taking into account peer behaviour and expression was obtained for the computation of the probability of channel- satisfactory ...

The role of subjective norms in theory of planned behavior in the context of organic food consumption

OpenAIRE

Al-Swidi, Abdullah; Huque, Sheikh Mohammed Rafiul; Hafeez, Muhammad Haroon; Shariff, Mohd Noor Mohd

2014-01-01

The purpose of the paper is to investigate the applicability of theory of planned behavior (TPB) with special emphasis on measuring the direct and moderating effect of subjective norms on attitude, perceived behavioral control and buying intention in context of buying organic food. Structured questionnaires were randomly distributed among academic staffs and students of two universities in southern Punjab, Pakistan. Structural equation modeling was employed to test the proposed model fit....

Poisson statistics of PageRank probabilities of Twitter and Wikipedia networks

Science.gov (United States)

Frahm, Klaus M.; Shepelyansky, Dima L.

2014-04-01

We use the methods of quantum chaos and Random Matrix Theory for analysis of statistical fluctuations of PageRank probabilities in directed networks. In this approach the effective energy levels are given by a logarithm of PageRank probability at a given node. After the standard energy level unfolding procedure we establish that the nearest spacing distribution of PageRank probabilities is described by the Poisson law typical for integrable quantum systems. Our studies are done for the Twitter network and three networks of Wikipedia editions in English, French and German. We argue that due to absence of level repulsion the PageRank order of nearby nodes can be easily interchanged. The obtained Poisson law implies that the nearby PageRank probabilities fluctuate as random independent variables.

The Probability of Detection in the Telephone Line of Device of the Unauthorized Removal of Information

Directory of Open Access Journals (Sweden)

I. V. Svintsov

2011-06-01

Full Text Available The article discusses the theory of quantitative description of the possible presence in the telephone line devices unauthorized removal of information, investigated with the help of probability theory.

Situated technology in reproductive health care: Do we need a new theory of the subject to promote person-centred care?

Science.gov (United States)

Stankovic, Biljana

2017-01-01

Going through reproductive experiences (especially pregnancy and childbirth) in contemporary Western societies almost inevitably involves interaction with medical practitioners and various medical technologies in institutional context. This has important consequences for women as embodied subjects. A critical appraisal of these consequences-coming dominantly from feminist scholarship-relied on a problematic theory of both technology and the subject, which are in contemporary approaches no longer considered as given, coherent and well individualized wholes, but as complex constellations that are locally situated and that can only be described empirically. In this study, we will be relying on the developments in phenomenological theory to reconceptualize women as technologically mediated embodied subjects and on the new paradigms in philosophy of technology and STS to reconstruct medical technology as situated-with the aim of reconceptualizing their relationship and exploring different possibilities for the mediating role of medical technology. It will be argued that technologization of female reproductive processes and alienating consequences for women are not necessary or directly interrelated. The role of technology varies from case to case and depends mainly on the nontechnological and relational aspects of institutional context, in which medical practitioners play a decisive role. © 2016 John Wiley & Sons Ltd.

The Valuation of Insurance under Uncertainty: Does Information about Probability Matter?

OpenAIRE

Carmela Di Mauro; Anna Maffioletti

2001-01-01

In a laboratory experiment we test the hypothesis that consumers' valuation of insurance is sensitive to the amount of information available on the probability of a potential loss. In order to test this hypothesis we simulate a market in which we elicit individuals' willingness to pay to insure against a loss characterised either by known or else vague probabilities. We use two distinct treatments by providing subjects with different information over the vague probabilities of loss. In genera...

Applying Probability Theory for the Quality Assessment of a Wildfire Spread Prediction Framework Based on Genetic Algorithms

Directory of Open Access Journals (Sweden)

Andrés Cencerrado

2013-01-01

Full Text Available This work presents a framework for assessing how the existing constraints at the time of attending an ongoing forest fire affect simulation results, both in terms of quality (accuracy obtained and the time needed to make a decision. In the wildfire spread simulation and prediction area, it is essential to properly exploit the computational power offered by new computing advances. For this purpose, we rely on a two-stage prediction process to enhance the quality of traditional predictions, taking advantage of parallel computing. This strategy is based on an adjustment stage which is carried out by a well-known evolutionary technique: Genetic Algorithms. The core of this framework is evaluated according to the probability theory principles. Thus, a strong statistical study is presented and oriented towards the characterization of such an adjustment technique in order to help the operation managers deal with the two aspects previously mentioned: time and quality. The experimental work in this paper is based on a region in Spain which is one of the most prone to forest fires: El Cap de Creus.

Determination of bounds on failure probability in the presence of ...

Indian Academy of Sciences (India)

In particular, fuzzy set theory provides a more rational framework for ..... indicating that the random variations inT andO2 do not affect failure probability significantly. ... The upper-bound for PF shown in figure 6 can be used in decision-making.

Strong lensing probability in TeVeS (tensor–vector–scalar) theory

International Nuclear Information System (INIS)

Chen Daming

2008-01-01

We recalculate the strong lensing probability as a function of the image separation in TeVeS (tensor–vector–scalar) cosmology, which is a relativistic version of MOND (MOdified Newtonian Dynamics). The lens is modeled by the Hernquist profile. We assume an open cosmology with Ω b = 0.04 and Ω Λ = 0.5 and three different kinds of interpolating functions. Two different galaxy stellar mass functions (GSMF) are adopted: PHJ (Panter, Heavens and Jimenez 2004 Mon. Not. R. Astron. Soc. 355 764) determined from SDSS data release 1 and Fontana (Fontana et al 2006 Astron. Astrophys. 459 745) from GOODS-MUSIC catalog. We compare our results with both the predicted probabilities for lenses from singular isothermal sphere galaxy halos in LCDM (Lambda cold dark matter) with a Schechter-fit velocity function, and the observational results for the well defined combined sample of the Cosmic Lens All-Sky Survey (CLASS) and Jodrell Bank/Very Large Array Astrometric Survey (JVAS). It turns out that the interpolating function μ(x) = x/(1+x) combined with Fontana GSMF matches the results from CLASS/JVAS quite well

Entanglement probabilities of polymers: a white noise functional approach

International Nuclear Information System (INIS)

Bernido, Christopher C; Carpio-Bernido, M Victoria

2003-01-01

The entanglement probabilities for a highly flexible polymer to wind n times around a straight polymer are evaluated using white noise analysis. To introduce the white noise functional approach, the one-dimensional random walk problem is taken as an example. The polymer entanglement scenario, viewed as a random walk on a plane, is then treated and the entanglement probabilities are obtained for a magnetic flux confined along the straight polymer, and a case where an entangled polymer is subjected to the potential V = f-dot(s)θ. In the absence of the magnetic flux and the potential V, the entanglement probabilities reduce to a result obtained by Wiegel

Chern-Simons Theory, Matrix Models, and Topological Strings

International Nuclear Information System (INIS)

Walcher, J

2006-01-01

This book is a find. Marino meets the challenge of filling in less than 200 pages the need for an accessible review of topological gauge/gravity duality. He is one of the pioneers of the subject and a clear expositor. It is no surprise that reading this book is a great pleasure. The existence of dualities between gauge theories and theories of gravity remains one of the most surprising recent discoveries in mathematical physics. While it is probably fair to say that we do not yet understand the full reach of such a relation, the impressive amount of evidence that has accumulated over the past years can be regarded as a substitute for a proof, and will certainly help to delineate the question of what is the most fundamental quantum mechanical theory. Here is a brief summary of the book. The journey begins with matrix models and an introduction to various techniques for the computation of integrals including perturbative expansion, large-N approximation, saddle point analysis, and the method of orthogonal polynomials. The second chapter, on Chern-Simons theory, is the longest and probably the most complete one in the book. Starting from the action we meet Wilson loop observables, the associated perturbative 3-manifold invariants, Witten's exact solution via the canonical duality to WZW models, the framing ambiguity, as well as a collection of results on knot invariants that can be derived from Chern-Simons theory and the combinatorics of U (∞) representation theory. The chapter also contains a careful derivation of the large-N expansion of the Chern-Simons partition function, which forms the cornerstone of its interpretation as a closed string theory. Finally, we learn that Chern-Simons theory can sometimes also be represented as a matrix model. The story then turns to the gravity side, with an introduction to topological sigma models (chapter 3) and topological string theory (chapter 4). While this presentation is necessarily rather condensed (and the beginner may

Assessment of climate change using methods of mathematic statistics and theory of probability

International Nuclear Information System (INIS)

Trajanoska, Lidija; Kaevski, Ivancho

2004-01-01

In simple terms: 'Climate' is the average of 'weather'. The Earth's weather system is a complex machine composed of coupled sub-systems (ocean, air, land, ice and the biosphere) between which energy are exchanged. The understanding and study of climate change does not only rely on the understanding of the physics of climate change but is linked to the following question: 'How we can detect change in a system that is changing all the time under its own volition'? What is even the meaning of 'change' in such a situation? The concept of 'change' we should transform into the concept of 'significant and long-term' then this re-phrasing allows for a definition in mathematical terms. Significant change in a system becomes a measure of how large an observed change is in terms of the variability one would see under 'normal' conditions. Example could be the analyses of the yearly temperature of the air and precipitations, like in this paper. A large amount of data are selected as representing the 'before' case (change) and another set of data are selected as being the 'after' case and then the average in these two cases are compared. These comparisons are in the form of 'hypothesis tests' in which one tests whether the hypothesis that there has Open no change can be rejected. Both parameter and nonparametric statistic methods are used in the theory of mathematic statistic. The most indicative changeable which show global change is an average, standard deviation and probability function distribution on examined time series. Examined meteorological series are taken like haphazard process so we can mathematic statistic applied.(Author)

Flu Shots, Mammogram, and the Perception of Probabilities

NARCIS (Netherlands)

Carman, K.G.; Kooreman, P.

2010-01-01

We study individuals’ decisions to decline or accept preventive health care interventions such as flu shots and mammograms. In particular, we analyze the role of perceptions of the effectiveness of the intervention, by eliciting individuals' subjective probabilities of sickness and survival, with

Probability, statistics, and computational science.

Science.gov (United States)

Beerenwinkel, Niko; Siebourg, Juliane

2012-01-01

In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters.

Levy's zero-one law in game-theoretic probability

OpenAIRE

Shafer, Glenn; Vovk, Vladimir; Takemura, Akimichi

2009-01-01

We prove a game-theoretic version of Levy's zero-one law, and deduce several corollaries from it, including non-stochastic versions of Kolmogorov's zero-one law, the ergodicity of Bernoulli shifts, and a zero-one law for dependent trials. Our secondary goal is to explore the basic definitions of game-theoretic probability theory, with Levy's zero-one law serving a useful role.

Probability and Statistics in Aerospace Engineering

Science.gov (United States)

Rheinfurth, M. H.; Howell, L. W.

1998-01-01

This monograph was prepared to give the practicing engineer a clear understanding of probability and statistics with special consideration to problems frequently encountered in aerospace engineering. It is conceived to be both a desktop reference and a refresher for aerospace engineers in government and industry. It could also be used as a supplement to standard texts for in-house training courses on the subject.

Heart sounds analysis using probability assessment

Czech Academy of Sciences Publication Activity Database

Plešinger, Filip; Viščor, Ivo; Halámek, Josef; Jurčo, Juraj; Jurák, Pavel

2017-01-01

Roč. 38, č. 8 (2017), s. 1685-1700 ISSN 0967-3334 R&D Projects: GA ČR GAP102/12/2034; GA MŠk(CZ) LO1212; GA MŠk ED0017/01/01 Institutional support: RVO:68081731 Keywords : heart sounds * FFT * machine learning * signal averaging * probability assessment Subject RIV: FS - Medical Facilities ; Equipment OBOR OECD: Medical engineering Impact factor: 2.058, year: 2016

A measure of mutual divergence among a number of probability distributions

Directory of Open Access Journals (Sweden)

J. N. Kapur

1987-01-01

major inequalities due to Shannon, Renyi and Holder. The inequalities are then used to obtain some useful results in information theory. In particular measures are obtained to measure the mutual divergence among two or more probability distributions.

Modern graph theory

CERN Document Server

Bollobás, Béla

1998-01-01

The time has now come when graph theory should be part of the education of every serious student of mathematics and computer science, both for its own sake and to enhance the appreciation of mathematics as a whole. This book is an in-depth account of graph theory, written with such a student in mind; it reflects the current state of the subject and emphasizes connections with other branches of pure mathematics. The volume grew out of the author's earlier book, Graph Theory -- An Introductory Course, but its length is well over twice that of its predecessor, allowing it to reveal many exciting new developments in the subject. Recognizing that graph theory is one of several courses competing for the attention of a student, the book contains extensive descriptive passages designed to convey the flavor of the subject and to arouse interest. In addition to a modern treatment of the classical areas of graph theory such as coloring, matching, extremal theory, and algebraic graph theory, the book presents a detailed ...

Bias and spread in extreme value theory measurements of probability of error

Science.gov (United States)

Smith, J. G.

1972-01-01

Extreme value theory is examined to explain the cause of the bias and spread in performance of communications systems characterized by low bit rates and high data reliability requirements, for cases in which underlying noise is Gaussian or perturbed Gaussian. Experimental verification is presented and procedures that minimize these effects are suggested. Even under these conditions, however, extreme value theory test results are not particularly more significant than bit error rate tests.

Lectures on probability and statistics

International Nuclear Information System (INIS)

Yost, G.P.

1984-09-01

These notes are based on a set of statistics lectures delivered at Imperial College to the first-year postgraduate students in High Energy Physics. They are designed for the professional experimental scientist. We begin with the fundamentals of probability theory, in which one makes statements about the set of possible outcomes of an experiment, based upon a complete a priori understanding of the experiment. For example, in a roll of a set of (fair) dice, one understands a priori that any given side of each die is equally likely to turn up. From that, we can calculate the probability of any specified outcome. We finish with the inverse problem, statistics. Here, one begins with a set of actual data (e.g., the outcomes of a number of rolls of the dice), and attempts to make inferences about the state of nature which gave those data (e.g., the likelihood of seeing any given side of any given die turn up). This is a much more difficult problem, of course, and one's solutions often turn out to be unsatisfactory in one respect or another

Elements of the theory of Markov processes and their applications

CERN Document Server

Bharucha-Reid, A T

2010-01-01

This graduate-level text and reference in probability, with numerous applications to several fields of science, presents nonmeasure-theoretic introduction to theory of Markov processes. The work also covers mathematical models based on the theory, employed in various applied fields. Prerequisites are a knowledge of elementary probability theory, mathematical statistics, and analysis. Appendixes. Bibliographies. 1960 edition.

Theory of random sets

CERN Document Server

Molchanov, Ilya

2017-01-01

This monograph, now in a thoroughly revised second edition, offers the latest research on random sets. It has been extended to include substantial developments achieved since 2005, some of them motivated by applications of random sets to econometrics and finance. The present volume builds on the foundations laid by Matheron and others, including the vast advances in stochastic geometry, probability theory, set-valued analysis, and statistical inference. It shows the various interdisciplinary relationships of random set theory within other parts of mathematics, and at the same time fixes terminology and notation that often vary in the literature, establishing it as a natural part of modern probability theory and providing a platform for future development. It is completely self-contained, systematic and exhaustive, with the full proofs that are necessary to gain insight. Aimed at research level, Theory of Random Sets will be an invaluable reference for probabilists; mathematicians working in convex and integ...

End-to-end probability for an interacting center vortex world line in Yang-Mills theory

International Nuclear Information System (INIS)

Teixeira, Bruno F.I.; Lemos, Andre L.L. de; Oxman, Luis E.

2011-01-01

Full text: The understanding of quark confinement is a very important open problem in Yang-Mills theory. In this regard, nontrivial topological defects are expected to play a relevant role to achieve a solution. Here we are interested in how to deal with these structures, relying on the Cho-Faddeev-Niemi decomposition and the possibility it offers to describe defects in terms of a local color frame. In particular, the path integral for a single center vortex is a fundamental object to handle the ensemble integration. As is well-known, in three dimensions center vortices are string-like and the associated physics is closely related with that of polymers. Using recent techniques developed in the latter context, we present in this work a detailed derivation of the equation for the end-to-end probability for a center vortex world line, including the effects of interactions. Its solution can be associated with a Green function that depends on the position and orientation at the boundaries, where monopole-like instantons are placed. In the limit of semi flexible polymers, an expansion only keeping the lower angular momenta for the final orientation leads to a reduced Green function for a complex vortex field minimally coupled to the dual Yang-Mills fields. This constitutes a key ingredient to propose an effective model for correlated monopoles, center vortices and the dual fields. (author)

Modeling Stochastic Complexity in Complex Adaptive Systems: Non-Kolmogorov Probability and the Process Algebra Approach.

Science.gov (United States)

Sulis, William H

2017-10-01

Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.

Recommendations for the tuning of rare event probability estimators

International Nuclear Information System (INIS)

Balesdent, Mathieu; Morio, Jérôme; Marzat, Julien

2015-01-01

Being able to accurately estimate rare event probabilities is a challenging issue in order to improve the reliability of complex systems. Several powerful methods such as importance sampling, importance splitting or extreme value theory have been proposed in order to reduce the computational cost and to improve the accuracy of extreme probability estimation. However, the performance of these methods is highly correlated with the choice of tuning parameters, which are very difficult to determine. In order to highlight recommended tunings for such methods, an empirical campaign of automatic tuning on a set of representative test cases is conducted for splitting methods. It allows to provide a reduced set of tuning parameters that may lead to the reliable estimation of rare event probability for various problems. The relevance of the obtained result is assessed on a series of real-world aerospace problems

Modeling and measuring the effects of imprecision using fuzzy theory and bayesian theory

International Nuclear Information System (INIS)

Yu, Dong Han; Park, Won S.

1999-01-01

This study presents two approaches for evaluating the imprecision inherent in the PRA. Current PRA methodology uses expert opinion in the assessment of rare event probabilities. The problem is that these probabilities may be difficult to estimate even though reasonable engineering judgment is applied. This occurs because expert opinion under incomplete knowledge and limited data is inherently imprecise and uncertain in the analysis of severe accident management. In this case, the concept of uncertainty about a probability value, namely the high-order uncertainty, would be both intuitively appealing and potentially useful. This analysis considers first an accident management as a decision problem (i.e., 'applying a strategy' vs. 'do nothing') and uses an influence diagram. Then, the analysis applies two approaches to evaluate imprecise node probabilities in the influence diagram: 'a fuzzy probability' and 'an interval-valued subjective probability'. For the propagation of subjective probabilities, the analysis uses the Monte-Carlo simulation. In case of fuzzy probabilities, the fuzzy logic is applied to propagate them. We believe that these approaches can allow us to understand uncertainties associated with severe accident management strategy since they offer additional information regarding the impact from imprecise input data

The exact probability distribution of the rank product statistics for replicated experiments.

Science.gov (United States)

Eisinga, Rob; Breitling, Rainer; Heskes, Tom

2013-03-18

The rank product method is a widely accepted technique for detecting differentially regulated genes in replicated microarray experiments. To approximate the sampling distribution of the rank product statistic, the original publication proposed a permutation approach, whereas recently an alternative approximation based on the continuous gamma distribution was suggested. However, both approximations are imperfect for estimating small tail probabilities. In this paper we relate the rank product statistic to number theory and provide a derivation of its exact probability distribution and the true tail probabilities. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Quantum Zeno and anti-Zeno effects measured by transition probabilities

Energy Technology Data Exchange (ETDEWEB)

Zhang, Wenxian, E-mail: wxzhang@whu.edu.cn [School of Physics and Technology, Wuhan University, Wuhan, Hubei 430072 (China); Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Kavli Institute for Theoretical Physics China, CAS, Beijing 100190 (China); Kofman, A.G. [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States); Zhuang, Jun [Department of Optical Science and Engineering, Fudan University, Shanghai 200433 (China); You, J.Q. [Beijing Computational Science Research Center, Beijing 10084 (China); Department of Physics, Fudan University, Shanghai 200433 (China); CEMS, RIKEN, Saitama 351-0198 (Japan); Nori, Franco [CEMS, RIKEN, Saitama 351-0198 (Japan); Department of Physics, The University of Michigan, Ann Arbor, MI 48109-1040 (United States)

2013-10-30

Using numerical calculations, we compare the transition probabilities of many spins in random magnetic fields, subject to either frequent projective measurements, frequent phase modulations, or a mix of modulations and measurements. For various distribution functions, we find the transition probability under frequent modulations is suppressed most if the pulse delay is short and the evolution time is larger than a critical value. Furthermore, decay freezing occurs only under frequent modulations as the pulse delay approaches zero. In the large pulse-delay region, however, the transition probabilities under frequent modulations are highest among the three control methods.

Prediction of accident sequence probabilities in a nuclear power plant due to earthquake events

International Nuclear Information System (INIS)

Hudson, J.M.; Collins, J.D.

1980-01-01

This paper presents a methodology to predict accident probabilities in nuclear power plants subject to earthquakes. The resulting computer program accesses response data to compute component failure probabilities using fragility functions. Using logical failure definitions for systems, and the calculated component failure probabilities, initiating event and safety system failure probabilities are synthesized. The incorporation of accident sequence expressions allows the calculation of terminal event probabilities. Accident sequences, with their occurrence probabilities, are finally coupled to a specific release category. A unique aspect of the methodology is an analytical procedure for calculating top event probabilities based on the correlated failure of primary events

Approximations to the Probability of Failure in Random Vibration by Integral Equation Methods

DEFF Research Database (Denmark)

Nielsen, Søren R.K.; Sørensen, John Dalsgaard

Close approximations to the first passage probability of failure in random vibration can be obtained by integral equation methods. A simple relation exists between the first passage probability density function and the distribution function for the time interval spent below a barrier before...... passage probability density. The results of the theory agree well with simulation results for narrow banded processes dominated by a single frequency, as well as for bimodal processes with 2 dominating frequencies in the structural response....... outcrossing. An integral equation for the probability density function of the time interval is formulated, and adequate approximations for the kernel are suggested. The kernel approximation results in approximate solutions for the probability density function of the time interval, and hence for the first...

Dynamic random walks theory and applications

CERN Document Server

Guillotin-Plantard, Nadine

2006-01-01

The aim of this book is to report on the progress realized in probability theory in the field of dynamic random walks and to present applications in computer science, mathematical physics and finance. Each chapter contains didactical material as well as more advanced technical sections. Few appendices will help refreshing memories (if necessary!).· New probabilistic model, new results in probability theory· Original applications in computer science· Applications in mathematical physics· Applications in finance

Statistical utility theory for comparison of nuclear versus fossil power plant alternatives

International Nuclear Information System (INIS)

Garribba, S.; Ovi, A.

1977-01-01

A statistical formulation of utility theory is developed for decision problems concerned with the choice among alternative strategies in electric energy production. Four alternatives are considered: nuclear power, fossil power, solar energy, and conservation policy. Attention is focused on a public electric utility thought of as a rational decision-maker. A framework for decisions is then suggested where the admissible strategies and their possible consequences represent the information available to the decision-maker. Once the objectives of the decision process are assessed, consequences can be quantified in terms of measures of effectiveness. Maximum expected utility is the criterion of choice among alternatives. Steps toward expected values are the evaluation of the multidimensional utility function and the assessment of subjective probabilities for consequences. In this respect, the multiplicative form of the utility function seems less restrictive than the additive form and almost as manageable to implement. Probabilities are expressed through subjective marginal probability density functions given at a discrete number of points. The final stage of the decision model is to establish the value of each strategy. To this scope, expected utilities are computed and scaled. The result is that nuclear power offers the best alternative. 8 figures, 9 tables, 32 references

Frequency, probability, and prediction: easy solutions to cognitive illusions?

Science.gov (United States)

Griffin, D; Buehler, R

1999-02-01

Many errors in probabilistic judgment have been attributed to people's inability to think in statistical terms when faced with information about a single case. Prior theoretical analyses and empirical results imply that the errors associated with case-specific reasoning may be reduced when people make frequentistic predictions about a set of cases. In studies of three previously identified cognitive biases, we find that frequency-based predictions are different from-but no better than-case-specific judgments of probability. First, in studies of the "planning fallacy, " we compare the accuracy of aggregate frequency and case-specific probability judgments in predictions of students' real-life projects. When aggregate and single-case predictions are collected from different respondents, there is little difference between the two: Both are overly optimistic and show little predictive validity. However, in within-subject comparisons, the aggregate judgments are significantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general knowledge and base rate neglect in categorical prediction underline a general conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. Copyright 1999 Academic Press.