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      1. Naturvetenskap och teknik
      2. Matematik och naturvetenskap
      3. Matematik
      4. Matematisk statistik

      Probabilistic Analysis of Belief Functions

      AvIvan Kramosil

      Inbunden, Engelska, 2001

      Del i serien IFSR International Series in Systems Science and Systems Engineering

      1 094 kr

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      Fler format och utgåvor

      Häftad

      1 092 kr

      E-bok

      1 413 kr

      Beskrivning

      This volume is a theoretical and mathematical study analyzing the notion and theory of belief functions, also known as the Dempster-Shafer theory, from the point of view of the classical Kolmogorov axiomatic probability theory. In other terms, the theory of belief functions is taken as a non-traditional application of probability theory, and the standard methodology of probability theory, and measure theory in general, is applied in order to arrive at some new and perhaps interesting generalizations and results not accessible within the classical combinatorial framework of the theory of belief functions (Dempster-Shafer theory) over finite spaces. The relation to great systems and their theory seems to be very close and should become clear from the first two chapters of the book.

      Produktinformation

      • Utgivningsdatum:2001-12-31
      • Mått:155 x 235 x undefined mm
      • Format:Inbunden
      • Språk:Engelska
      • Serie:IFSR International Series in Systems Science and Systems Engineering
      • Antal sidor:214
      • Förlag:Springer Science+Business Media
      • ISBN:9780306467028

      Utforska kategorier

      • Matematisk statistik inom Naturvetenskap och teknik
      • Tillämpad matematik inom Naturvetenskap och teknik

      Innehållsförteckning

      • 1 Introduction.- 1.1 Uncertainty in the World Around.- 1.2 Classical Probability Theory - Uncertainty as Randomness.- 1.3 Dempster-Shafer Approach to Uncertainty Processing.- 1.4 Relations to the Theory of General Systems.- 2 Preliminaries on Axiomatic Probability Theory.- 2.1 Probability Spaces and Random Variables.- 2.2 Some Intuition and Motivation Behind.- 2.3 Conditional Probabilities and Stochastic Independence.- 2.4 The Most Simple Setting of the Strong Law of Large Numbers.- 3 Probabilistic Model of Decision Making under Uncertainty.- 3.1 An Intuitive Background to Decision Making Theory.- 3.2 Decision Making under Uncertainty.- 3.3 Statistical Decision Functions.- 3.4 The Bayesian and the Minimax Principles.- 3.5 An Example and Some Problems Involved.- 4 Basic Elements of Dempster-Shafer Theory.- 4.1 From Intuition to Compatibility Relations.- 4.2 From Compatibility Relations to Belief Functions.- 4.3 Some Remarks and Comments.- 4.4 Semantical Consistence and Correctness of Belief Functions.- 5 Elementary Properties of Belief Functions.- 5.1 Plausibility Functions.- 5.2 Basic Probability Assignments and Belief Functions.- 5.3 Super-Additivity of Belief Functions.- 5.4 Some Particular Cases of Belief Functions.- 5.5 Belief Functions and the Case of Total Ignorance.- 6 Probabilistic Analysis of Dempster Combination Rule.- 6.1 Knowledge Acquisition as Dynamical Process.- 6.2 Combining Compatibility Relations.- 6.3 Towards Dempster Combination Rule.- 6.4 Elementary Properties of Dempster Combination Rule.- 6.5 Dual Combination Rule.- 7 Nonspecificity Degrees of Basic Probability Assignments.- 7.1 The Most Simple Case of Nonspecificity Degrees.- 7.2 Nonspecificity Degrees of Dempster Products.- 7.3 Quasi-Deconditioning.- 7.4 The Case of Dual Combination Rule.- 8 Belief Functions Induced by Partial Compatibility Relations.- 8.1 Compatibility Relations over Sets of States and Sets of Empirical Values.- 8.2 Partial Generalized Compatibility Relations.- 8.3 Belief Functions Defined by Partial Generalized Compatibility Relations.- 8.4 Partial Generalized Compatibility Relations with the Same Compatibility Relation.- 8.5 Approximations of Belief Functions by the Partial Generalized Ones.- 9 Belief Functions over Infinite State Spaces.- 9.1 Towards Infinite Basic Spaces.- 9.2 Definability of Degrees of Belief for Subsets of Infinite Spaces.- 9.3 Extensions of Degrees of Belief to Non-Regular Subsets.- 9.4 Elementary Properties of Extended Belief Functions.- 9.5 Bounds of Application of Extended Belief Functions.- 9.6 Survey of Approximations of Degrees of Belief over Infinite Spaces.- 10 Boolean Combinations of Set-Valued Random Variables.- 10.1 Combining Set-Valued Random Variables.- 10.2 Belief Functions Defined by Unions of Set-Valued Random Variables.- 10.3 Belief Functions Defined by Intersections of Set-Valued Random Variables.- 11 Belief Functions with Signed and Nonstandard Values.- 11.1 The Inversion Problem for Degrees of Belief and Belief Functions.- 11.2 Signed Measures.- 11.3 Degrees of Belief Are Leaving the Unit Interval of Reals.- 11.4 Dempster Combination Rule for Basic Signed Measure Assignments.- 11.5 Inversion Rule for Basic Signed Measure Assignments.- 11.6 Almost Invertibility of Basic Signed Measure Assignments.- 11.7 Degrees of Belief with Nonstandard Values.- 11.8 An Abstract Algebraic Approach to the Inversion Problem.- 12 Jordan Decomposition of Signed Belief Functions.- 12.1 Hahn Decomposition Theorem for Signed Measures.- 12.2 Jordan Decomposition of Signed Belief Functions.- 12.3 Generalizing Conditioned Belief Functions.- 13 Monte-Carlo Estimations for Belief Functions.- 13.1 Strong Law of Large Numbers Applied to Belief Functions.- 13.2 Towards Monte-Carlo Algorithms for Belief Functions.- 13.3 Asymptotic Properties of Monte-Carlo Estimations of Belief Functions.- 13.4 Chebyshev Inequality for Monte-Carlo Estimations of Belief Functions.- 14 Boolean-Valued and Boolean-Like Processed Belief Functions.- 14.1 Intuition, Motivation and Preliminaries on Boolean Algebras.- 14.2 Boolean-Valued Probability Measures.- 14.3 Boolean-Valued Belief and Plausibility Functions.- 14.4 Boolean-Like Structure over The Unit Interval of Real Numbers.- 14.5 Probability Measures with Values in Boolean-Like Structured Unit Interval of Real Numbers.- 14.6 Basic Nonstandard Probability Assignments.- 15 References.- 16 Index.
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