In probability theory, Bayesian statistics, artificial intelligence and database theory the minimum cross-entropy principle is often used to estimate a distribution with a given set P of marginal distributions under the proportionality assumption with respect to a given “prior” distribution q. Such an estimation problem admits a solution if and only if there exists an extension of P that is dom...

In this paper, we consider the problem of regression analysis for data which consist of a large number of independent small groups or clusters of correlated observations. Instead of using the standard mean regression, we regress various percentiles of each marginal response variable over its covariates to obtain a more accurate assessment of the covariate effect. Our inference procedures are de...

The aim of this work is studying the use of copulas and vines in numerical optimization with Estimation of Distribution Algorithms (EDAs). Two EDAs built around the multivariate product and normal copulas, and other two based on pair-copula decomposition of vine models are studied. We analyze empirically the effect of both marginal distributions and dependence structure in order to show that bo...

A Corporation is a company that owns other companies outstanding stock. In business matters, a Corporation is a defaul company if, at least, one of its subsidiary is on default. The statistical interest is, in a specific period of time, to determine the Default probability for the Corporation given that the subsidiaries of this Corporation are correlated. Therefore, the model must address the i...

In this article, we provide a template for the practical implementation of the targeted maximum likelihood estimator for analyzing causal effects of multiple time point interventions, for which the methodology was developed and presented in Part I. In addition, the application of this template is demonstrated in two important estimation problems: estimation of the effect of individualized treat...

In normative public economics it is crucial to know how fast the marginal utility of income declines as income increases. One needs this parameter for cost-benefit analysis, for optimal taxation and for the (Atkinson) measurement of inequality. We estimate this parameter using four large cross-sectional surveys of subjective happiness and two panel surveys. Altogether, the data cover over 50 co...

This note considers the treatment of risk and uncertainty in the recently established ‘social cost of carbon’ (SCC) for analysis of federal regulations in the United States. It argues that the analysis of the US Interagency Working Group on Social Cost of Carbon did not go far enough into the tail of low-probability, high-impact scenarios, and, via its approach to discounting, it mis-estimated ...

Saarela et al. are concerned with integrating propensity scores into a Bayesian framework. Some of us have previously written (Robins and Ritov, 1997; Robins and Wasserman, 2000; http://normaldeviate.wordpress.com/2012/08/28/robins-and-wasserman-respond-to-a-nobelprize-winner/; posted 28 Aug 2012, accessed 1 Oct 2014) about this topic, every time making much the same argument. Here we present a...

Longitudinal studies in which exposures, confounders, and outcomes are measured repeatedly over time have the potential to allow causal inferences about the effects of exposure on outcome. There is particular interest in estimating the causal effects of medical treatments (or other interventions) in circumstances in which a randomized controlled trial is difficult or impossible. However, standa...

Marginal regression modeling with generalised estimating equations became very popular in the last decade. While the mean structure is of primary interest in rst-order generalised estimating equations (GEE1), second-order generalised estimating equations (GEE2) allow the estimation of both the mean and the association structure. It has repeatedly been shown that the usual robust variance estima...