Titlebook: Advances in Statistical Models for Data Analysis; Isabella Morlini,Tommaso Minerva,Maurizio Vichi Conference proceedings 2015 Springer Int

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不能仁慈

Robust Clustering of EU Banking Data,ize, business activities and geographical location. After the latest financial crisis, it has become of paramount importance for European regulators to identify common features and issues in the EU banking system and address them in all Member States (or at least those of the Euro area) in a harmoni

yohimbine

Sovereign Risk and Contagion Effects in the Eurozone: A Bayesian Stochastic Correlation Model,ing the recent financial crisis. We follow an MCMC approach to parameters and latent variable estimation and provide evidence of significant volatility shifts in asset returns, strong simultaneous increases in cross-market correlations, as well as sharp declines in correlations patterns. Overall, th

不能约

Female Labour Force Participation and Selection Effect: Southern vs Eastern European Countries,ross the four European countries (Italy, Greece, Hungary and Poland) with the lowest female labour force participation. The potential bias due to the overlap in some unobserved characteristics is addressed via a bivariate probit model. Significant selection effects of opposite signs are found for th

Arthritis

Asymptotics in Survey Sampling for High Entropy Sampling Designs,rical process based on the Hájek estimator of the population distribution function and then extended to Hadamard-differentiable functions. As an application, asymptotic normality of estimated quantiles is provided.

ELUC

A Note on the Use of Recursive Partitioning in Causal Inference,sed on a multidimensional balance measure criterion applied to the values of the covariates to recursively split the data. Starting from an ad-hoc resampling scheme, observations are finally partitioned in subsets characterized by different degrees of homogeneity, and causal inference is carried out

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MAPLE

Families of Parsimonious Finite Mixtures of Regression Models,ls can be conveniently used for unsupervised learning on data with clear regression relationships. We extend such models by imposing an eigen-decomposition on the multivariate error covariance matrix. By constraining parts of this decomposition, we obtain families of parsimonious mixtures of regress

Popcorn

Quantile Regression for Clustering and Modeling Data, that allows to focus on the effects that a set of explanatory variables has on the entire conditional distribution of a dependent variable. The proposal concerns the use of multivariate techniques to simultaneously cluster and model data and it is illustrated using an empirical analysis. This analy