Forms of a World : Contemporary Poetry and the Making of Globalization / / Walt Hunter

• Record Nr.: UNINA9910479892603321
• Autore: Hunter Walt
• Pubbl/distr/stampa: New York, NY : , : Fordham University Press, , [2019]; ©2019
• ISBN: 0-8232-8607-X; 0-8232-8224-4; 0-8232-8223-6
• Edizione: [First edition.]
• Descrizione fisica: 1 online resource (201 pages)
• Collana: Fordham scholarship online
• Disciplina: 809/.933553
• Soggetti: Literature and globalization; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: This edition also issued in print: 2019.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Front matter -- Contents -- Introduction -- 1. Stolen Landscapes: The Investments of the Ode and the Politics of Land -- 2. Let Us Go: Lyric and the Transit of Citizenship -- 3. The Crowd to Come: Poetic Exhortations from Brooklyn to Kashmir -- 4. The No-Prospect Poem: Poetic Views of the Anthropocene -- Coda -- Acknowledgments -- Notes -- Bibliography -- Index
• Sommario/riassunto: What happens when we think of poetry as a global literary form, while also thinking the global in poetic terms? Forms of a World shows how the innovations of contemporary poetics have been forged through the transformations of globalization across five decades. Sensing the changes wrought by neoliberalism before they are made fully present, poets from around the world have creatively intervened in global processes by remaking poetry’s formal repertoire. In experimental reinventions of the ballad, the prospect poem, and the ode, Hunter excavates a new, globalized interpretation of the ethical and political relevance of forms. Forms of a World contends that poetry’s role is not only to make visible thematically the violence of global dispossessions, but to renew performatively the missing conditions for intervening within these processes. Poetic acts—the rhetoric of possessing, ; belonging, exhorting, and prospecting—address contemporary conditions that render social life ever more precarious. Examining an eclectic group of Anglophone poets, from Seamus Heaney and Claudia Rankine to Natasha Trethewey and Kofi Awoonor, Hunter elaborates the range of ways that contemporary poets exhort us to imagine forms of social life and enable political intervention unique to but beyond the horizon of the contemporary global situation.

Contemporary Bayesian econometrics and statistics [[electronic resource] /] / John Geweke

• Record Nr.: UNINA9910145035003321
• Autore: Geweke John
• Pubbl/distr/stampa: Hoboken, N.J., : John Wiley, c2005
• ISBN: 1-280-27761-0; 9786610277612; 0-470-23694-9; 0-471-74473-5; 0-471-74472-7
• Descrizione fisica: 1 online resource (322 p.)
• Collana: Wiley Series in Probability and Statistics ; ; v.537
• Disciplina: 330.015195; 330.01519542; 330/.01/519542
• Soggetti: Econometrics; Bayesian statistical decision theory; Decision making - Mathematical models; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Contemporary Bayesian Econometrics and Statistics; Contents; Preface; 1. Introduction; 1.1 Two Examples; 1.1.1 Public School Class Sizes; 1.1.2 Value at Risk; 1.2 Observables, Unobservables, and Objects of Interest; 1.3 Conditioning and Updating; 1.4 Simulators; 1.5 Modeling; 1.6 Decisionmaking; 2. Elements of Bayesian Inference; 2.1 Basics; 2.2 ; Sufficiency, Ancillarity, and Nuisance Parameters; 2.2.1 Sufficiency; 2.2.2 Ancillarity; 2.2.3 Nuisance Parameters; 2.3 Conjugate Prior Distributions; 2.4 Bayesian Decision Theory and Point Estimation; 2.5 Credible Sets; 2.6 Model Comparison; 2.6.1 Marginal Likelihoods2.6.2 Predictive Densities; 3. Topics in Bayesian Inference; 3.1 Hierarchical Priors and Latent Variables; 3.2 Improper Prior Distributions; 3.3 Prior Robustness and the Density Ratio Class; 3.4 Asymptotic Analysis; 3.5 The Likelihood Principle; 4. Posterior Simulation; 4.1 Direct Sampling; 4.2 Acceptance and Importance Sampling; 4.2.1 Acceptance Sampling; 4.2.2 Importance Sampling; 4.3 Markov Chain Monte Carlo; 4.3.1 The Gibbs Sampler; 4.3.2 The Metropolis-Hastings Algorithm; 4.4 Variance Reduction; 4.4.1 Concentrated Expectations; 4.4.2 Antithetic Sampling; 4.5 Some Continuous State Space Markov Chain Theory4.5.1 Convergence of the Gibbs Sampler; 4.5.2 Convergence of the Metropolis-Hastings Algorithm; 4.6 Hybrid Markov Chain Monte Carlo Methods; 4.6.1 Transition Mixtures; 4.6.2 Metropolis within Gibbs; 4.7 Numerical Accuracy and Convergence in Markov Chain Monte Carlo; 5. Linear Models; 5.1 BACC and the Normal Linear Regression Model; 5.2 Seemingly Unrelated Regressions Models; 5.3 Linear Constraints in the Linear Model; 5.3.1 Linear Inequality Constraints; 5.3.2 Conjectured Linear Restrictions, Linear Inequality Constraints, and Covariate Selection5.4 Nonlinear Regression; 5.4.1 Nonlinear Regression with Smoothness Priors; 5.4.2 Nonlinear Regression with Basis Functions; 6. Modeling with Latent Variables; 6.1 Censored Normal Linear Models; 6.2 Probit Linear Models; 6.3 The Independent Finite State Model; 6.4 Modeling with Mixtures of Normal Distributions; 6.4.1 The Independent Student-t Linear Model; 6.4.2 Normal Mixture Linear Models; 6.4.3 Generalizing the Observable Outcomes; 7. Modeling for Time Series; 7.1 Linear Models with Serial Correlation7.2 The First-Order Markov Finite State Model; 7.2.1 Inference in the Nonstationary Model; 7.2.2 Inference in the Stationary Model; 7.3 Markov Normal Mixture Linear Model; 8. Bayesian Investigation; 8.1 Implementing Simulation Methods; 8.1.1 Density Ratio Tests; 8.1.2 Joint Distribution Tests; 8.2 Formal Model Comparison; 8.2.1 Bayes Factors for Modeling with Common Likelihoods; 8.2.2 Marginal Likelihood Approximation Using Importance Sampling; 8.2.3 Marginal Likelihood Approximation Using Gibbs Sampling; 8.2.4 Density Ratio Marginal Likelihood Approximation
• Sommario/riassunto: Tools to improve decision making in an imperfect worldThis publication provides readers with a thorough understanding of Bayesian analysis that is grounded in the theory of inference and optimal decision making. Contemporary Bayesian Econometrics and Statistics provides readers with state-of-the-art simulation methods and models that are used to solve complex real-world problems. Armed with a strong foundation in both theory and practical problem-solving tools, readers discover how to optimize decision making when faced with problems that involve limited or imperfect data.The b