A Distributional (Single) Index Model (DIM) is a semiparametric model for distributional regression, that is, estimation of conditional distributions given covariates. The method combination classical single-index models the mean response covariates, and isotonic regression. index parametric, whereas are estimated nonparametrically under stochastic ordering constraint. We show consistency our e...

• Connections in Rn . We have by now defined a number of different notions of differentiation: the differential of maps between manifolds, the exterior derivative of differential forms, and the Lie derivative. To begin to see the need for a new notion of differentiation (which will turn out to be the most fundamental and will apply to general tensor fields) consider first the problem of definin...

How does fiscal austerity affect redistributive policies? We document that during episodes, countries tend to increase marginal income tax rates on top earners, but not average earners. then show that, in response an exogenously imposed rule, Italian municipalities local non-linear taxes progressively. They do adjust other policies. College-educated mayors are more likely than less educated imp...

The making of statistical inferences in distributional form is conceptionally complicated because the epistemic 'probabilities' assigned are mixtures of fact and fiction. In this respect they are essentially different from 'physical' or 'frequency-theoretic' probabilities. The distributional form is so attractive and useful, however, that it should be pursued. Our approach is In line with Walds...

We examine individuals’ distributional orderings in a number of contexts. This is done by using a questionnaire-experiment that is presented to respondents in any one of seven “flavours” or interpretations of the basic distributional problem. The flavours include inequality, risk, social welfare and justice. The issue of personal involvement in the distributional comparison is explicitly addres...

Distributional similarity is a useful notion in estimating the probabilities of rare joint events. It has been employed both to cluster events according to their distributions, and to directly compute averages of estimates for distributional neighbors of a target event. Here, we examine the tradeoffs between model size and prediction accuracy for cluster-based and nearest neighbors distribution...

385 EIsevier Note Îï the distributional complexity of disjointness Abstract Razborov, À.À., Îï the distributional complexity of disjointness, Theoretical Computer ScienCe 106 (1992) 385-390. We prove that the distributional communication complexity of the predicate "disjointness" with respect to à very simple measure îï inputs is Ùï).