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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 | ||
| ||
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 | ||
| ||
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-9911019800403321 |
| [Place of publication not identified], : Wiley, 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
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 | ||
| ||
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 | ||
| ||
Data analysis in forensic science [[electronic resource] ] : a Bayesian decision perspective / / Franco Taroni ... [et al.]
| Data analysis in forensic science [[electronic resource] ] : a Bayesian decision perspective / / Franco Taroni ... [et al.] |
| Pubbl/distr/stampa | Chichester, : John Wiley and Sons, 2010 |
| Descrizione fisica | 1 online resource (389 p.) |
| Disciplina | 363.2501/519542 |
| Altri autori (Persone) | TaroniFranco |
| Collana | Statistics in practice |
| Soggetto topico |
Forensic sciences - Statistical methods
Bayesian statistical decision theory |
| ISBN |
1-282-54840-9
9786612548406 0-470-66508-4 0-470-66507-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Data Analysis in Forensic Science; Contents; Foreword; Preface; I The Foundations of Inference and Decision in Forensic Science; 1 Introduction; 1.1 The Inevitability of Uncertainty; 1.2 Desiderata in Evidential Assessment; 1.3 The Importance of the Propositional Framework and the Nature of Evidential Assessment; 1.4 From Desiderata to Applications; 1.5 The Bayesian Core of Forensic Science; 1.6 Structure of the Book; 2 Scientific Reasoning and Decision Making; 2.1 Coherent Reasoning Under Uncertainty; 2.1.1 A rational betting policy; 2.1.2 A rational policy for combining degrees of belief
2.1.3 A rational policy for changing degrees of belief2.2 Coherent Decision Making Under Uncertainty; 2.2.1 A method for measuring the value of consequences; 2.2.2 The consequences of rational preferences; 2.2.3 Intermezzo: some more thoughts about rational preferences; 2.2.4 The implementation of coherent decision making under uncertainty: Bayesian networks; 2.2.5 The connection between pragmatic and epistemic standards of reasoning; 2.3 Scientific Reasoning as Coherent Decision Making; 2.3.1 Bayes' theorem; 2.3.2 The theories' race; 2.3.3 Statistical reasoning: the models' race 2.3.4 Probabilistic model building: betting on random quantities2.4 Forensic Reasoning as Coherent Decision Making; 2.4.1 Likelihood ratios and the 'weight of evidence'; 2.4.2 The expected value of information; 2.4.3 The hypotheses' race in the law; 3 Concepts of Statistical Science and Decision Theory; 3.1 Random Variables and Distribution Functions; 3.1.1 Univariate random variables; 3.1.2 Measures of location and variability; 3.1.3 Multiple random variables; 3.2 Statistical Inference and Decision Theory; 3.2.1 Utility theory; 3.2.2 Maximizing expected utility; 3.2.3 The loss function 3.3 The Bayesian Paradigm3.3.1 Sequential use of Bayes' theorem; 3.3.2 Principles of rational inference in statistics; 3.3.3 Prior distributions; 3.3.4 Predictive distributions; 3.3.5 Markov Chain Monte Carlo methods (MCMC); 3.4 Bayesian Decision Theory; 3.4.1 Optimal decisions; 3.4.2 Standard loss functions; 3.5 R Code; II Forensic Data Analysis; 4 Point Estimation; 4.1 Introduction; 4.2 Bayesian Decision for a Proportion; 4.2.1 Estimation when there are zero occurrences in a sample; 4.2.2 Prior probabilities; 4.2.3 Prediction 4.2.4 Inference for 0 in the presence of background data on the number of successes4.2.5 Multinomial variables; 4.3 Bayesian Decision for a Poisson Mean; 4.3.1 Inference about the Poisson parameter in the absence of background events; 4.3.2 Inference about the Poisson parameter in the presence of background events; 4.3.3 Forensic inference using graphical models; 4.4 Bayesian Decision for Normal Mean; 4.4.1 Case with known variance; 4.4.2 Case with unknown variance; 4.4.3 Estimation of the mean in the presence of background data; 4.5 R Code; 5 Credible Intervals; 5.1 Introduction 5.2 Credible Intervals and Lower Bounds |
| Record Nr. | UNINA-9910140587703321 |
| Chichester, : John Wiley and Sons, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data analysis in forensic science : a Bayesian decision perspective / / Franco Taroni ... [et al.]
| Data analysis in forensic science : a Bayesian decision perspective / / Franco Taroni ... [et al.] |
| Pubbl/distr/stampa | Chichester, : John Wiley and Sons, 2010 |
| Descrizione fisica | 1 online resource (389 p.) |
| Disciplina | 363.2501/519542 |
| Altri autori (Persone) | TaroniFranco |
| Collana | Statistics in practice |
| Soggetto topico |
Forensic sciences - Statistical methods
Bayesian statistical decision theory |
| ISBN |
9786612548406
9781282548404 1282548409 9780470665084 0470665084 9780470665077 0470665076 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Data Analysis in Forensic Science; Contents; Foreword; Preface; I The Foundations of Inference and Decision in Forensic Science; 1 Introduction; 1.1 The Inevitability of Uncertainty; 1.2 Desiderata in Evidential Assessment; 1.3 The Importance of the Propositional Framework and the Nature of Evidential Assessment; 1.4 From Desiderata to Applications; 1.5 The Bayesian Core of Forensic Science; 1.6 Structure of the Book; 2 Scientific Reasoning and Decision Making; 2.1 Coherent Reasoning Under Uncertainty; 2.1.1 A rational betting policy; 2.1.2 A rational policy for combining degrees of belief
2.1.3 A rational policy for changing degrees of belief2.2 Coherent Decision Making Under Uncertainty; 2.2.1 A method for measuring the value of consequences; 2.2.2 The consequences of rational preferences; 2.2.3 Intermezzo: some more thoughts about rational preferences; 2.2.4 The implementation of coherent decision making under uncertainty: Bayesian networks; 2.2.5 The connection between pragmatic and epistemic standards of reasoning; 2.3 Scientific Reasoning as Coherent Decision Making; 2.3.1 Bayes' theorem; 2.3.2 The theories' race; 2.3.3 Statistical reasoning: the models' race 2.3.4 Probabilistic model building: betting on random quantities2.4 Forensic Reasoning as Coherent Decision Making; 2.4.1 Likelihood ratios and the 'weight of evidence'; 2.4.2 The expected value of information; 2.4.3 The hypotheses' race in the law; 3 Concepts of Statistical Science and Decision Theory; 3.1 Random Variables and Distribution Functions; 3.1.1 Univariate random variables; 3.1.2 Measures of location and variability; 3.1.3 Multiple random variables; 3.2 Statistical Inference and Decision Theory; 3.2.1 Utility theory; 3.2.2 Maximizing expected utility; 3.2.3 The loss function 3.3 The Bayesian Paradigm3.3.1 Sequential use of Bayes' theorem; 3.3.2 Principles of rational inference in statistics; 3.3.3 Prior distributions; 3.3.4 Predictive distributions; 3.3.5 Markov Chain Monte Carlo methods (MCMC); 3.4 Bayesian Decision Theory; 3.4.1 Optimal decisions; 3.4.2 Standard loss functions; 3.5 R Code; II Forensic Data Analysis; 4 Point Estimation; 4.1 Introduction; 4.2 Bayesian Decision for a Proportion; 4.2.1 Estimation when there are zero occurrences in a sample; 4.2.2 Prior probabilities; 4.2.3 Prediction 4.2.4 Inference for 0 in the presence of background data on the number of successes4.2.5 Multinomial variables; 4.3 Bayesian Decision for a Poisson Mean; 4.3.1 Inference about the Poisson parameter in the absence of background events; 4.3.2 Inference about the Poisson parameter in the presence of background events; 4.3.3 Forensic inference using graphical models; 4.4 Bayesian Decision for Normal Mean; 4.4.1 Case with known variance; 4.4.2 Case with unknown variance; 4.4.3 Estimation of the mean in the presence of background data; 4.5 R Code; 5 Credible Intervals; 5.1 Introduction 5.2 Credible Intervals and Lower Bounds |
| Record Nr. | UNINA-9910814422903321 |
| Chichester, : John Wiley and Sons, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||