1.

Record Nr.

UNINA9910452350603321

Autore

Goodman Robin Truth <1966->

Titolo

Infertilities [[electronic resource] ] : exploring fictions of barren bodies / / Robin Truth Goodman

Pubbl/distr/stampa

Minneapolis, : University of Minnesota Press, c2001

ISBN

0-8166-9104-5

0-8166-3488-2

Descrizione fisica

xxiv, 234 p

Collana

Cultural studies of the Americas ; ; v. 4

Disciplina

863.009/353

Soggetti

Spanish American fiction - History and criticism

Infertility, Female, in literature

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references (p. 211-227) and index.



2.

Record Nr.

UNINA9910795434303321

Autore

Read Rupert J. <1966->

Titolo

Philosophy for life / / Rupert Read, edited by M. A. Lavery

Pubbl/distr/stampa

London, England ; ; New York, New York : , : Continuum, , 2007

©2007

ISBN

1-4411-6255-0

Edizione

[1st ed.]

Descrizione fisica

1 online resource (178 pages)

Disciplina

128

Soggetti

Ethics

Conduct of life

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Environment -- Religion -- Politics -- Art.

Sommario/riassunto

Philosophy for Life is a bold call for the practice of philosophy in our everyday lives. Philosopher and writer Rupert Read explores a series of important and often provocative contemporary political and cultural issues from a philosophical perspective, arguing that philosophy is not a body of doctrine, but a practice, a vantage point from which life should be analysed and, more importantly, acted upon.   Philosophy for Life is a personal journey that explores four key areas of society today: Politics, Religion, Art, and the Environment. Taking tangible examples from modern politics, from climate change to the war on terror, and culture, from Peter Jackson's Lord of the Rings film trilogy to the poetry of T.S. Eliot, Read shows that philosophy is already an active part of today's world. This captivating and timely book offers a philosophical response to some of the key questions facing today's society and encourages us to use philosophy as a kind of therapy. Philosophy for Life shows that we can improve our perspective on the world and our place in it by doing philosophy everyday.



3.

Record Nr.

UNINA9910155548503321

Titolo

Advanced Statistical Methods in Data Science / / edited by Ding-Geng Chen, Jiahua Chen, Xuewen Lu, Grace Y. Yi, Hao Yu

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2016

Edizione

[1st ed. 2016.]

Descrizione fisica

1 online resource (XVI, 222 p. 41 illus., 20 illus. in color.)

Collana

ICSA Book Series in Statistics, , 2199-0999

Disciplina

519.50285

Soggetti

Statistics

Quantitative research

Statistical Theory and Methods

Data Analysis and Big Data

Statistics in Business, Management, Economics, Finance, Insurance

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references at the end of each chapters and index.

Nota di contenuto

Part I: Data Analysis Based on Latent or Dependent Variable Models -- Chapter 1: A New Method for Robust Mixture Regression and Outlier Detection -- Chapter 2: The Mixture Gatekeeping Procedure Based on Weighted Multiple Testing Correction for Correlated Tests -- Chapter 3: Regularization in Regime-switching Gaussian Autoregressive Models -- Chapter 4: Modeling Zero Inflation and Over-dispersion in the Length of Hospital Stay for Patients with Ischaemic Heart Disease -- Chapter 5: Robust Optimal Interval Design for High-Dimensional Dose Finding in Multi-Agent Combination Trials -- Part II: Life Time Data Analysis -- Chapter 6: Group Selection in Semi-parametric Accelerated Failure Time Model -- Chapter 7: A Proportional Odds Model for Regression Analysis of Case I Interval-Censored Data -- Chapter 8: Empirical Likelihood Inference under Density Ratio Models Based on Type I Censored Samples: Hypothesis Testing and Quantile Estimation -- Chapter 9: Recent Development in the Joint Modeling of Longitudinal Quality of Life Measurements and Survival Data from Cancer Clinical Trials -- Part III: Applied Data Analysis -- Chapter 10: Confidence Weighting Procedures for Multiple Choice Tests -- Chapter 11: Improving the Robustness of Parametric Imputation -- Chapter 12: Maximum



Smoothed Likelihood Estimation of the Centre of a Symmetric Distribution -- Chapter 13: Dividend Pay-out Problems with the Logarithmic Utility -- Chapter 14: Modeling the Common Risk among Equities: A Multivariate Time Series Model with an Additive GARCH Structure.

Sommario/riassunto

This book gathers invited presentations from the 2nd Symposium of the ICSA- CANADA Chapter held at the University of Calgary from August 4-6, 2015. The aim of this Symposium was to promote advanced statistical methods in big-data sciences and to allow researchers to exchange ideas on statistics and data science and to embraces the challenges and opportunities of statistics and data science in the modern world.  It addresses diverse themes in advanced statistical analysis in big-data sciences, including methods for administrative data analysis, survival data analysis, missing data analysis, high-dimensional and genetic data analysis, longitudinal and functional data analysis, the design and analysis of studies with response-dependent and multi-phase designs, time series and robust statistics, statistical inference based on likelihood, empirical likelihood and estimating functions. The editorial group selected 14 high-quality presentations from this successful symposium and invitedthe presenters to prepare a full chapter for this book in order to disseminate the findings and promote further research collaborations in this area. This timely book offers new methods that impact advanced statistical model development in big-data sciences.