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Bayesian networks and probabilistic inference in forensic science
Bayesian networks and probabilistic inference in forensic science
Pubbl/distr/stampa [Place of publication not identified], : Wiley, 2006
Disciplina 363.2501/519542
Collana Statistics in practice Bayesian networks and probabilistic inference in forensic science
Soggetto topico Bayesian statistical decision theory - Graphic methods
Uncertainty (Information theory) - Graphic methods
Forensic sciences - Graphic methods
Mathematical Statistics
Mathematics
Physical Sciences & Mathematics
ISBN 0-470-09175-4
0-470-09174-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto The logic of uncertainty -- The logic of Bayesian networks -- Evaluation of scientific evidence -- Bayesian networks for evaluating scientific evidence -- DNA evidence -- Transfer evidence -- Aspects of the combination of evidence -- Pre-assessment -- Qualitative and sensitivity analyses -- Continuous networks -- Further applications.
Record Nr. UNINA-9910144723503321
[Place of publication not identified], : Wiley, 2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian networks and probabilistic inference in forensic science
Bayesian networks and probabilistic inference in forensic science
Pubbl/distr/stampa [Place of publication not identified], : Wiley, 2006
Disciplina 363.2501/519542
Collana Statistics in practice Bayesian networks and probabilistic inference in forensic science
Soggetto topico Bayesian statistical decision theory - Graphic methods
Uncertainty (Information theory) - Graphic methods
Forensic sciences - Graphic methods
Mathematical Statistics
Mathematics
Physical Sciences & Mathematics
ISBN 0-470-09175-4
0-470-09174-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto The logic of uncertainty -- The logic of Bayesian networks -- Evaluation of scientific evidence -- Bayesian networks for evaluating scientific evidence -- DNA evidence -- Transfer evidence -- Aspects of the combination of evidence -- Pre-assessment -- Qualitative and sensitivity analyses -- Continuous networks -- Further applications.
Record Nr. UNINA-9910830744003321
[Place of publication not identified], : Wiley, 2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian networks and probabilistic inference in forensic science
Bayesian networks and probabilistic inference in forensic science
Pubbl/distr/stampa [Place of publication not identified], : Wiley, 2006
Disciplina 363.2501/519542
Collana Statistics in practice Bayesian networks and probabilistic inference in forensic science
Soggetto topico Bayesian statistical decision theory - Graphic methods
Uncertainty (Information theory) - Graphic methods
Forensic sciences - Graphic methods
Mathematical Statistics
Mathematics
Physical Sciences & Mathematics
ISBN 0-470-09175-4
0-470-09174-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto The logic of uncertainty -- The logic of Bayesian networks -- Evaluation of scientific evidence -- Bayesian networks for evaluating scientific evidence -- DNA evidence -- Transfer evidence -- Aspects of the combination of evidence -- Pre-assessment -- Qualitative and sensitivity analyses -- Continuous networks -- Further applications.
Record Nr. UNINA-9910877313003321
[Place of publication not identified], : Wiley, 2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian networks for probabilistic inference and decision analysis in forensic science / / Franco Taroni [and four others]
Bayesian networks for probabilistic inference and decision analysis in forensic science / / Franco Taroni [and four others]
Edizione [2nd ed.]
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2014
Descrizione fisica 1 online resource (473 p.)
Disciplina 363.2501/519542
Collana Statistics in Practice
Soggetto topico Bayesian statistical decision theory - Graphic methods
Uncertainty (Information theory) - Graphic methods
Forensic sciences - Graphic methods
ISBN 1-118-91476-7
1-118-91475-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Foreword; Preface to the second edition; Preface to the first edition; Chapter 1 The logic of decision; 1.1 Uncertainty and probability; 1.1.1 Probability is not about numbers, it is about coherent reasoning under uncertainty; 1.1.2 The first two laws of probability; 1.1.3 Relevance and independence; 1.1.4 The third law of probability; 1.1.5 Extension of the conversation; 1.1.6 Bayes' theorem; 1.1.7 Probability trees; 1.1.8 Likelihood and probability; 1.1.9 The calculus of (probable) truths; 1.2 Reasoning under uncertainty
1.2.1 The Hound of the Baskervilles1.2.2 Combination of background information and evidence; 1.2.3 The odds form of Bayes' theorem; 1.2.4 Combination of evidence; 1.2.5 Reasoning with total evidence; 1.2.6 Reasoning with uncertain evidence; 1.3 Population proportions, probabilities and induction; 1.3.1 The statistical syllogism; 1.3.2 Expectations and population proportions; 1.3.3 Probabilistic explanations; 1.3.4 Abduction and inference to the best explanation; 1.3.5 Induction the Bayesian way; 1.4 Decision making under uncertainty; 1.4.1 Bookmakers in the Courtrooms?; 1.4.2 Utility theory
1.4.3 The rule of maximizing expected utility1.4.4 The loss function; 1.4.5 Decision trees; 1.4.6 The expected value of information; 1.5 Further readings; Chapter 2 The logic of Bayesian networks and influence diagrams; 2.1 Reasoning with graphical models; 2.1.1 Beyond detective stories; 2.1.2 Bayesian networks; 2.1.3 A graphical model for relevance; 2.1.4 Conditional independence; 2.1.5 Graphical models for conditional independence: d-separation; 2.1.6 A decision rule for conditional independence; 2.1.7 Networks for evidential reasoning; 2.1.8 The Markov property; 2.1.9 Influence diagrams
2.1.10 Conditional independence in influence diagrams2.1.11 Relevance and causality; 2.1.12 The Hound of the Baskervilles revisited; 2.2 Reasoning with Bayesian networks and influence diagrams; 2.2.1 Divide and conquer; 2.2.2 From directed to triangulated graphs; 2.2.3 From triangulated graphs to junction trees; 2.2.4 Solving influence diagrams; 2.2.5 Object-oriented Bayesian networks; 2.2.6 Solving object-oriented Bayesian networks; 2.3 Further readings; 2.3.1 General; 2.3.2 Bayesian networks and their predecessors in judicial contexts
Chapter 3 Evaluation of scientific findings in forensic science3.1 Introduction; 3.2 The value of scientific findings; 3.3 Principles of forensic evaluation and relevant propositions; 3.3.1 Source level propositions; 3.3.1.1 Notation; 3.3.1.2 Single stain; 3.3.2 Activity level propositions; 3.3.2.1 Notation and formulaic development; 3.3.3 Crime level propositions; 3.3.3.1 Notation; 3.3.3.2 Association propositions; 3.3.3.3 Intermediate association propositions; 3.4 Pre-assessment of the case; 3.5 Evaluation using graphical models; 3.5.1 Introduction
3.5.2 General aspects of the construction of Bayesian networks
Record Nr. UNINA-9910132177003321
Chichester, England : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Bayesian networks for probabilistic inference and decision analysis in forensic science / / Franco Taroni [and four others]
Bayesian networks for probabilistic inference and decision analysis in forensic science / / Franco Taroni [and four others]
Edizione [2nd ed.]
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2014
Descrizione fisica 1 online resource (473 p.)
Disciplina 363.2501/519542
Collana Statistics in Practice
Soggetto topico Bayesian statistical decision theory - Graphic methods
Uncertainty (Information theory) - Graphic methods
Forensic sciences - Graphic methods
ISBN 1-118-91476-7
1-118-91475-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Foreword; Preface to the second edition; Preface to the first edition; Chapter 1 The logic of decision; 1.1 Uncertainty and probability; 1.1.1 Probability is not about numbers, it is about coherent reasoning under uncertainty; 1.1.2 The first two laws of probability; 1.1.3 Relevance and independence; 1.1.4 The third law of probability; 1.1.5 Extension of the conversation; 1.1.6 Bayes' theorem; 1.1.7 Probability trees; 1.1.8 Likelihood and probability; 1.1.9 The calculus of (probable) truths; 1.2 Reasoning under uncertainty
1.2.1 The Hound of the Baskervilles1.2.2 Combination of background information and evidence; 1.2.3 The odds form of Bayes' theorem; 1.2.4 Combination of evidence; 1.2.5 Reasoning with total evidence; 1.2.6 Reasoning with uncertain evidence; 1.3 Population proportions, probabilities and induction; 1.3.1 The statistical syllogism; 1.3.2 Expectations and population proportions; 1.3.3 Probabilistic explanations; 1.3.4 Abduction and inference to the best explanation; 1.3.5 Induction the Bayesian way; 1.4 Decision making under uncertainty; 1.4.1 Bookmakers in the Courtrooms?; 1.4.2 Utility theory
1.4.3 The rule of maximizing expected utility1.4.4 The loss function; 1.4.5 Decision trees; 1.4.6 The expected value of information; 1.5 Further readings; Chapter 2 The logic of Bayesian networks and influence diagrams; 2.1 Reasoning with graphical models; 2.1.1 Beyond detective stories; 2.1.2 Bayesian networks; 2.1.3 A graphical model for relevance; 2.1.4 Conditional independence; 2.1.5 Graphical models for conditional independence: d-separation; 2.1.6 A decision rule for conditional independence; 2.1.7 Networks for evidential reasoning; 2.1.8 The Markov property; 2.1.9 Influence diagrams
2.1.10 Conditional independence in influence diagrams2.1.11 Relevance and causality; 2.1.12 The Hound of the Baskervilles revisited; 2.2 Reasoning with Bayesian networks and influence diagrams; 2.2.1 Divide and conquer; 2.2.2 From directed to triangulated graphs; 2.2.3 From triangulated graphs to junction trees; 2.2.4 Solving influence diagrams; 2.2.5 Object-oriented Bayesian networks; 2.2.6 Solving object-oriented Bayesian networks; 2.3 Further readings; 2.3.1 General; 2.3.2 Bayesian networks and their predecessors in judicial contexts
Chapter 3 Evaluation of scientific findings in forensic science3.1 Introduction; 3.2 The value of scientific findings; 3.3 Principles of forensic evaluation and relevant propositions; 3.3.1 Source level propositions; 3.3.1.1 Notation; 3.3.1.2 Single stain; 3.3.2 Activity level propositions; 3.3.2.1 Notation and formulaic development; 3.3.3 Crime level propositions; 3.3.3.1 Notation; 3.3.3.2 Association propositions; 3.3.3.3 Intermediate association propositions; 3.4 Pre-assessment of the case; 3.5 Evaluation using graphical models; 3.5.1 Introduction
3.5.2 General aspects of the construction of Bayesian networks
Record Nr. UNINA-9910806181303321
Chichester, England : , : Wiley, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui