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1. |
Record Nr. |
UNINA9910141404103321 |
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Titolo |
Case studies in Bayesian statistical modelling and analysis [[electronic resource] /] / edited by Clair Alston, Kerrie Mengersen, and Anthony Pettitt |
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Pubbl/distr/stampa |
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Chichester, West Sussex, : John Wiley & Sons Inc., 2012 |
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ISBN |
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1-118-39447-X |
1-283-65634-5 |
1-118-39449-6 |
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Edizione |
[1st edition] |
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Descrizione fisica |
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1 online resource (499 p.) |
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Collana |
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Wiley Series in Probability and Statistics |
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Altri autori (Persone) |
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AlstonClair |
MengersenKerrie L |
PettittAnthony (Anthony N.) |
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Disciplina |
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Soggetti |
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Bayesian statistical decision theory |
Statistical decision |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Case Studies in Bayesian Statistical Modelling and Analysis; Contents; Preface; List of contributors; 1 Introduction; 1.1 Introduction; 1.2 Overview; 1.3 Further reading; 1.3.1 Bayesian theory and methodology; 1.3.2 Bayesian methodology; 1.3.3 Bayesian computation; 1.3.4 Bayesian software; 1.3.5 Applications; References; 2 Introduction to MCMC; 2.1 Introduction; 2.2 Gibbs sampling; 2.2.1 Example: Bivariate normal; 2.2.2 Example: Change-point model; 2.3 Metropolis-Hastings algorithms; 2.3.1 Example: Component-wise MH or MH within Gibbs; 2.3.2 Extensions to basic MCMC; 2.3.3 Adaptive MCMC |
2.3.4 Doubly intractable problems2.4 Approximate Bayesian computation; 2.5 Reversible jump MCMC; 2.6 MCMC for some further applications; References; 3 Priors: Silent or active partners of Bayesian inference?; 3.1 Priors in the very beginning; 3.1.1 Priors as a basis for learning; 3.1.2 Priors and philosophy; 3.1.3 Prior chronology; 3.1.4 Pooling prior information; 3.2 Methodology I: Priors defined by mathematical criteria; 3.2.1 Conjugate priors; 3.2.2 Impropriety and hierarchical priors; 3.2.3 Zellner's g-prior for regression models; 3.2.4 |
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Objective priors |
3.3 Methodology II: Modelling informative priors3.3.1 Informative modelling approaches; 3.3.2 Elicitation of distributions; 3.4 Case studies; 3.4.1 Normal likelihood: Time to submit research dissertations; 3.4.2 Binomial likelihood: Surveillance for exotic plant pests; 3.4.3 Mixture model likelihood: Bioregionalization; 3.4.4 Logistic regression likelihood: Mapping species distribution via habitat models; 3.5 Discussion; 3.5.1 Limitations; 3.5.2 Finding out about the problem; 3.5.3 Prior formulation; 3.5.4 Communication; 3.5.5 Conclusion; Acknowledgements; References |
4 Bayesian analysis of the normal linear regression model4.1 Introduction; 4.2 Case studies; 4.2.1 Case study 1: Boston housing data set; 4.2.2 Case study 2: Production of cars and station wagons; 4.3 Matrix notation and the likelihood; 4.4 Posterior inference; 4.4.1 Natural conjugate prior; 4.4.2 Alternative prior specifications; 4.4.3 Generalizations of the normal linear model; 4.4.4 Variable selection; 4.5 Analysis; 4.5.1 Case study 1: Boston housing data set; 4.5.2 Case study 2: Car production data set; References; 5 Adapting ICU mortality models for local data: A Bayesian approach |
5.1 Introduction5.2 Case study: Updating a known risk-adjustment model for local use; 5.3 Models and methods; 5.4 Data analysis and results; 5.4.1 Updating using the training data; 5.4.2 Updating the model yearly; 5.5 Discussion; References; 6 A Bayesian regression model with variable selection for genome-wide association studies; 6.1 Introduction; 6.2 Case study: Case-control of Type 1 diabetes; 6.3 Case study: GENICA; 6.4 Models and methods; 6.4.1 Main effect models; 6.4.2 Main effects and interactions; 6.5 Data analysis and results; 6.5.1 WTCCC TID; 6.5.2 GENICA; 6.6 Discussion |
Acknowledgements |
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Sommario/riassunto |
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Provides an accessible foundation to Bayesian analysis using real world models This book aims to present an introduction to Bayesian modelling and computation, by considering real case studies drawn from diverse fields spanning ecology, health, genetics and finance. Each chapter comprises a description of the problem, the corresponding model, the computational method, results and inferences as well as the issues that arise in the implementation of these approaches. Case Studies in Bayesian Statistical Modelling and Analysis: Illustrates how |
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2. |
Record Nr. |
UNINA9910787279503321 |
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Titolo |
Big data, open data, open source : Information and records management opportunities and challenges / / guest editor, Anne Thurston |
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Pubbl/distr/stampa |
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Bradford, [England] : , : Emerald Insight, , 2014 |
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©2014 |
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ISBN |
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Descrizione fisica |
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1 online resource (105 p.) |
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Collana |
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Records Management Journal, , 0956-5698 ; ; Volume 24, Issue 2 |
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Disciplina |
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Soggetti |
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Business records |
Records - Management |
Information storage and retrieval systems |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Cover; EDITORIAL ADVISORY BOARD; Editorial; Guest Editorial; The mapping, selecting and opening of data; Whither the retention schedule in the era of big data and open data?; Meeting Big Data challenges with visual analytics; Opening research data: issues and opportunities; Open data?; Book review |
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Sommario/riassunto |
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The world is experiencing a data revolution. The idea is that data can be used to drive and support development in both the public and the private sectors. This trend, I believe, has major implications for the records and archives profession. The Records Management Journal is taking a lead in initiating debate on this issue, recognizing that the records management community has an important role to play in the move toward Open Data and Big Data Analytics. If records managers can bring their skills and experience to the challenges of managing and protecting data integrity through time, they wil |
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3. |
Record Nr. |
UNINA9910781075703321 |
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Autore |
Sorenson John <1952-> |
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Titolo |
Ape [[electronic resource] /] / John Sorenson |
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Pubbl/distr/stampa |
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ISBN |
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1-282-79611-9 |
9786612796111 |
1-86189-746-4 |
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Descrizione fisica |
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1 online resource (226 p.) |
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Collana |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Ape Cover; Imprint page; Contents; 1 Natural History; 2 Thinking about Apes; 3 Pets, Captives, Hybrids; 4 Looking at Apes; 5 Models for Human Behaviour; 6 Extinction; Timeline of the Ape; References; Select Bibliography; Associations and Websites; Acknowledgements; Photo Acknowledgements; Index |
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Sommario/riassunto |
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Apes-to look at them is to see a mirror of ourselves. Our close genetic relatives fascinate and unnerve us with their similar behavior and social personality. Here, John Sorenson delves into our conflicted relationship to the great apes, which often revea |
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