Copulas (in English, the verb to be) are conventionally defined functionally as a means of relating elements of clause structure, especially subject and complement, and considered to be semantically empty or meaningless.They have received relatively little attention from linguists. Dr Pustet in this extensive cross-linguistic study goes some way towards correcting this neglect. In doing so she takes issue with both accepted definition and description. She presents an analysis of grammatical descriptions of over 160 languages drawn from the language families of the world. She shows that some languages have a single copula, others several, and some none at all. In a series of statistical analyses she seeks to explain why by linking the distribution of copulas to variations in lexical categorization and syntactic structure. She concludes by advancing a comprehensive theory of copularization which she relates to language classification and to theories of language change, notably grammaticalization.
3.2 3.3 3.4 3.5 3.6 Show that a version of the Marshall-Olkin bivariate distribution with Pareto margins (see Example 2.14) has joint survival functions given by H(x,y)=(1+x)" (1+y)*[max(1+x, 1+y)]”, for x,y 20, where 6, 6, ...
This book provides the reader with a background on simulating copulas and multivariate distributions in general.
Copula Modeling explores the copula approach for econometrics modeling of joint parametric distributions.
Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas.
This is a succinct guide to the application and modelling of dependence models or copulas in the financial markets.
... aggregation model. Canad. J. Statist. 43(1), 60–81 (2015) 7. Culhane, A.C., Perri`ere, G., Higgins, D.G.: Cross-platform comparison and visualisation of gene expression data using co-inertia analysis. BMC Bioinformatics 21, 4–59 (2003) ...
This book is about the theoretical and practical aspects of the statistics of Extreme Events in Nature. Most importantly, this is the first text in which Copulas are introduced and used in Geophysics.
The book explains the pair-copula construction principles underlying these statistical models and discusses how to perform model selection and inference.
(1) Predictive QQ plot The predictive quantile-quantile (QQ) plot provides an overall assessment of whether the total predictive uncertainty is consistent with the observations. This requires a diagnostic approach that compares a ...
The latest tools and techniques for pricing and risk management This book introduces readers to the use of copula functions to represent the dynamics of financial assets and risk factors, integrated temporal and cross-section applications.