03101nam 2200613 a 450 991078627020332120230803025507.00-8047-8558-910.1515/9780804785587(CKB)2670000000335592(EBL)1117240(OCoLC)827208530(SSID)ssj0000826806(PQKBManifestationID)12426850(PQKBTitleCode)TC0000826806(PQKBWorkID)10810081(PQKB)10781135(MiAaPQ)EBC1117240(DE-B1597)563763(DE-B1597)9780804785587(Au-PeEL)EBL1117240(CaPaEBR)ebr10651971(OCoLC)1178769972(EXLCZ)99267000000033559220121108d2013 uy 0engur||#||||||||txtccrAbout Europe[electronic resource] philosophical hypotheses /Denis Guénoun ; translated by Christine IrizarryStanford, Calif. Stanford University Press20131 online resource (353 p.)Cultural Memory in the PresentCultural memory in the present"Originally published in French under the title Hypothèses sur l'Europe: Un essai de philosophie."0-8047-7385-8 0-8047-7386-6 pt. I. Europe crossways -- pt. II. On national revolution -- pt. III. Transports of origin -- pt. IV. No returns.The concept of the universal was born in the lands we now call Europe, yet it is precisely the universal that is Europe's undoing. All European politics is caught in a tension: to assert a European identity is to be open to multiplicity, but this very openness could dissolve Europe as such. This book reflects on Europe and its changing boundaries over the span of twenty centuries. A work of philosophy, it consistently draws on concrete events. From ancient Greece and Rome, to Christianity, to the Reformation, to the national revolutions of the twentieth century, what we today call "Europe" has been a succession of projects in the name of ecclesia or community. Empire, Church, and EU: all have been constructed in contrast to an Oriental "other." The stakes of Europe, then, are as much metaphysical as political. Redefining a series of key concepts such as world, place, transportation, and the common, this book sheds light on Europe as process by engaging with the most significant philosophical debates on the subject, including the work of Marx, Husserl, Heidegger, Patočka, and Nancy.Cultural Memory in the PresentPHILOSOPHY / GeneralbisacshEuropeHistoryPhilosophyPHILOSOPHY / General.940.01Guénoun Denis1946-1330630Irizarry Christine1540994MiAaPQMiAaPQMiAaPQBOOK9910786270203321About Europe3792921UNINA04543nam 22006495 450 991073729520332120230911132950.03-031-32800-010.1007/978-3-031-32800-8(CKB)5700000000428112(MiAaPQ)EBC30702995(Au-PeEL)EBL30702995(DE-He213)978-3-031-32800-8(PPN)27227321X(OCoLC)1395078576(EXLCZ)99570000000042811220230816d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierGeneralized Linear Mixed Models with Applications in Agriculture and Biology[electronic resource] /by Josafhat Salinas Ruíz, Osval Antonio Montesinos López, Gabriela Hernández Ramírez, Jose Crossa Hiriart1st ed. 2023.Cham :Springer International Publishing :Imprint: Springer,2023.1 online resource (434 pages)3-031-32799-3 Chapter 1) Elements of the Generalized Linear Mixed Models -- Chapter 2) Generalized Linear Models -- Chapter 3) Objectives in Model Inference -- Chapter 4) Generalized Linear Mixed Models for non-normal responses -- Chapter 5) Generalized Linear Mixed Models for Count response -- Chapter 6) Generalized Linear Mixed Models for Proportions and Percentages response -- Chapter 7) Times of occurrence of an event of interest -- Chapter 8) Generalized Linear Mixed Models for Categorial and Ordinal responses -- Chapter 9) Generalized Linear Mixed Models for Repeated Measurements.This open access book offers an introduction to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that supports each of the studied methods is addressed and later - through examples - its application is illustrated. In addition, some of the assumptions and shortcomings of linear statistical models in general are also discussed. An alternative to analyse non-normal distributed response variables is the use of generalized linear models (GLM) to describe the response data with an exponential family distribution that perfectly fits the real response. Extending this idea to models with random effects allows the use of Generalized Linear Mixed Models (GLMMs). The use of these complex models was not computationally feasible until the recent past, when computational advances and improvements to statistical analysis programs allowed users to easily, quickly, and accurately apply GLMM to data sets. GLMMs have attracted considerable attention in recent years. The word "Generalized" refers to non-normal distributions for the response variable and the word "Mixed" refers to random effects, in addition to the fixed effects typical of analysis of variance (or regression). With the development of modern statistical packages such as Statistical Analysis System (SAS), R, ASReml, among others, a wide variety of statistical analyzes are available to a wider audience. However, to be able to handle and master more sophisticated models requires proper training and great responsibility on the part of the practitioner to understand how these advanced tools work. GMLM is an analysis methodology used in agriculture and biology that can accommodate complex correlation structures and types of response variables.BiometryMultivariate analysisRegression analysisAgricultureBiostatisticsMultivariate AnalysisLinear Models and RegressionAgricultureBiometry.Multivariate analysis.Regression analysis.Agriculture.Biostatistics.Multivariate Analysis.Linear Models and Regression.Agriculture.570.15195Salinas Ruíz Josafhat1424254Montesinos López Osval Antonio1078558Hernández Ramírez Gabriela1424255Crossa Hiriart Jose1424256MiAaPQMiAaPQMiAaPQBOOK9910737295203321Generalized Linear Mixed Models with Applications in Agriculture and Biology3553385UNINA