FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2167731203> ?p ?o ?g. }

• W2167731203 abstract "List of Figures. List of Tables. Preface. Acknowledgments. Introduction. Part I: Introducing Bayesian Analysis. 1. The foundations of Bayesian inference. 1.1 What is probability? 1.2 Subjective probability in Bayesian statistics. 1.3 Bayes theorem, discrete case. 1.4 Bayes theorem, continuous parameter. 1.5 Parameters as random variables, beliefs as distributions. 1.6 Communicating the results of a Bayesian analysis. 1.7 Asymptotic properties of posterior distributions. 1.8 Bayesian hypothesis testing. 1.9 From subjective beliefs to parameters and models. 1.10 Historical note. 2. Getting started: Bayesian analysis for simple models. 2.1 Learning about probabilities, rates and proportions. 2.2 Associations between binary variables. 2.3 Learning from counts. 2.4 Learning about a normal mean and variance. 2.5 Regression models. 2.6 Further reading. Part II: Simulation Based Bayesian Analysis. 3. Monte Carlo methods. 3.1 Simulation consistency. 3.2 Inference for functions of parameters. 3.3 Marginalization via Monte Carlo integration. 3.4 Sampling algorithms. 3.5 Further reading. 4. Markov chains. 4.1 Notation and definitions. 4.2 Properties of Markov chains. 4.3 Convergence of Markov chains. 4.4 Limit theorems for Markov chains. 4.5 Further reading. 5. Markov chain Monte Carlo. 5.1 Metropolis-Hastings algorithm. 5.2 Gibbs sampling. 6. Implementing Markov chain Monte Carlo. 6.1 Software for Markov chain Monte Carlo. 6.2 Assessing convergence and run-length. 6.3 Working with BUGS/JAGS from R. 6.4 Tricks of the trade. 6.5 Other examples. 6.6 Further reading. Part III: Advanced Applications in the Social Sciences. 7. Hierarchical Statistical Models. 7.1 Data and parameters that vary by groups: the case for hierarchical modeling. 7.2 ANOVA as a hierarchical model. 7.3 Hierarchical models for longitudinal data. 7.4 Hierarchical models for non-normal data. 7.5 Multi-level models. 8. Bayesian analysis of choice making. 8.1 Regression models for binary responses. 8.2 Ordered outcomes. 8.3 Multinomial outcomes. 8.4 Multinomial probit. 9. Bayesian approaches to measurement. 9.1 Bayesian inference for latent states. 9.2 Factor analysis. 9.3 Item-response models. 9.4 Dynamic measurement models. Part IV: Appendices. Appendix A: Working with vectors and matrices. Appendix B: Probability review. B.1 Foundations of probability. B.2 Probability densities and mass functions. B.3 Convergence of sequences of random variabales. Appendix C: Proofs of selected propositions. C.1 Products of normal densities. C.2 Conjugate analysis of normal data. C.3 Asymptotic normality of the posterior density. References. Topic index. Author index." @default.
• W2167731203 created "2016-06-24" @default.
• W2167731203 creator A5057360766 @default.
• W2167731203 date "2009-10-23" @default.
• W2167731203 modified "2023-10-11" @default.
• W2167731203 title "Bayesian Analysis for the Social Sciences" @default.
• W2167731203 cites W127422594 @default.
• W2167731203 cites W1514773669 @default.
• W2167731203 cites W1547322272 @default.
• W2167731203 cites W1548573677 @default.
• W2167731203 cites W1563505517 @default.
• W2167731203 cites W169775351 @default.
• W2167731203 cites W1828041481 @default.
• W2167731203 cites W1855309718 @default.
• W2167731203 cites W1967734402 @default.
• W2167731203 cites W1968269771 @default.
• W2167731203 cites W1975408228 @default.
• W2167731203 cites W1988520084 @default.
• W2167731203 cites W1994990033 @default.
• W2167731203 cites W1995453127 @default.
• W2167731203 cites W1997914622 @default.
• W2167731203 cites W2003706076 @default.
• W2167731203 cites W2004105083 @default.
• W2167731203 cites W2009274009 @default.
• W2167731203 cites W2018872781 @default.
• W2167731203 cites W2029791679 @default.
• W2167731203 cites W2035968557 @default.
• W2167731203 cites W2041995595 @default.
• W2167731203 cites W2044233129 @default.
• W2167731203 cites W2045141291 @default.
• W2167731203 cites W2045656233 @default.
• W2167731203 cites W2049633694 @default.
• W2167731203 cites W2050283732 @default.
• W2167731203 cites W2051257402 @default.
• W2167731203 cites W2054455128 @default.
• W2167731203 cites W2054673836 @default.
• W2167731203 cites W2071166009 @default.
• W2167731203 cites W2076411009 @default.
• W2167731203 cites W2084840427 @default.
• W2167731203 cites W2087577266 @default.
• W2167731203 cites W2092034922 @default.
• W2167731203 cites W2092052157 @default.
• W2167731203 cites W2092164462 @default.
• W2167731203 cites W2094438284 @default.
• W2167731203 cites W2095348470 @default.
• W2167731203 cites W2100784037 @default.
• W2167731203 cites W2101170002 @default.
• W2167731203 cites W2103502708 @default.
• W2167731203 cites W2120402364 @default.
• W2167731203 cites W2120695425 @default.
• W2167731203 cites W2123838014 @default.
• W2167731203 cites W2126163471 @default.
• W2167731203 cites W2143143555 @default.
• W2167731203 cites W2152977846 @default.
• W2167731203 cites W2156273867 @default.
• W2167731203 cites W2159740989 @default.
• W2167731203 cites W2160153783 @default.
• W2167731203 cites W2245735879 @default.
• W2167731203 cites W2313210471 @default.
• W2167731203 cites W2332423244 @default.
• W2167731203 cites W2483000999 @default.
• W2167731203 cites W2524620787 @default.
• W2167731203 cites W2764485636 @default.
• W2167731203 cites W2796369599 @default.
• W2167731203 cites W2969734899 @default.
• W2167731203 cites W306234367 @default.
• W2167731203 cites W3083113686 @default.
• W2167731203 cites W3128806671 @default.
• W2167731203 cites W3203633735 @default.
• W2167731203 cites W3821663 @default.
• W2167731203 cites W73375746 @default.
• W2167731203 cites W92160820 @default.
• W2167731203 doi "https://doi.org/10.1002/9780470686621" @default.
• W2167731203 hasPublicationYear "2009" @default.
• W2167731203 type Work @default.
• W2167731203 sameAs 2167731203 @default.
• W2167731203 citedByCount "554" @default.
• W2167731203 countsByYear W21677312032012 @default.
• W2167731203 countsByYear W21677312032013 @default.
• W2167731203 countsByYear W21677312032014 @default.
• W2167731203 countsByYear W21677312032015 @default.
• W2167731203 countsByYear W21677312032016 @default.
• W2167731203 countsByYear W21677312032017 @default.
• W2167731203 countsByYear W21677312032018 @default.
• W2167731203 countsByYear W21677312032019 @default.
• W2167731203 countsByYear W21677312032020 @default.
• W2167731203 countsByYear W21677312032021 @default.
• W2167731203 countsByYear W21677312032022 @default.
• W2167731203 countsByYear W21677312032023 @default.
• W2167731203 crossrefType "monograph" @default.
• W2167731203 hasAuthorship W2167731203A5057360766 @default.
• W2167731203 hasConcept C107673813 @default.
• W2167731203 hasConcept C144024400 @default.
• W2167731203 hasConcept C154945302 @default.
• W2167731203 hasConcept C2522767166 @default.
• W2167731203 hasConcept C41008148 @default.
• W2167731203 hasConceptScore W2167731203C107673813 @default.
• W2167731203 hasConceptScore W2167731203C144024400 @default.
• W2167731203 hasConceptScore W2167731203C154945302 @default.
• W2167731203 hasConceptScore W2167731203C2522767166 @default.

• next