Many conventional statistical procedures are extremely sensitive to seemingly minor deviations from modeling assumptions. This problem is exacerbated in modern high-dimensional settings, where the problem dimension can grow with and possibly exceed the sample size. We consider the problem of robust estimation of sparse functionals, and provide a computationally and statistically efficient algor...

This article introduces generalized beta-generated (GBG) distributions. Sub-models include all classical beta-generated, Kumaraswamy-generated and exponentiated distributions. They are maximum entropy distributions under three intuitive conditions, which show that the classical beta generator skewness parameters only control tail entropy and an additional shape parameter is needed to add entrop...

The completeness of a bond market model with infinite number of sources of randomness on a finite time interval in the Heath-Jarrow-Morton framework is studied. It is proved that the market in the case of trading strategies is not complete. An explicit construction of a bounded contingent claim, which can not be replicated, is provided. Moreover, a new concept of generalized strategies is intro...

In this paper we survey existing results concerning the joint distribution of the sequence of estimates of the parameter vector when a model is tted to accumulating data and we provide a uniied theory which explains the \independent increments" structure commonly seen in group sequential test statistics. Our theory covers normal linear models, including the case of correlated observations, and ...

r a 200 .061 : +64 4 3 iwa.co.n Summary This study is devoted to simulation of the interannual variability of daily rainfall, such as the mean and variance of seasonal rainfall totals and the correlation between seasonal rainfall totals and a seasonal climate variable (e.g., an index of atmospheric or oceanic circulation). Prior work established that a mixture of chain-dependent processes, invo...

We aim at proposing a Generalized Linear Model (GLM) with binary dependent variable Y , whose link function defined by the Generalized Extreme Value (GEV) distribution. We define this model as GEV regression. The goal of this paper is to overcome the drawbacks shown by the logistic regression in rare events: the probability of rare events is underestimated and the logit link is a symmetric func...

It is well known that using individual covariate information (such as body weight or gender) to model heterogeneity in capture–recapture (CR) experiments can greatly enhance inferences on the size of a closed population. Since individual covariates are only observable for captured individuals, complex conditional likelihood methods are usually required and these do not constitute a standard gen...

We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLM), a new class of methods for nonparametric regression. Given a data set of input-response pairs, the DP-GLM produces a global model of the joint distribution through a mixture of local generalized linear models. DP-GLMs allow both continuous and categorical inputs, and can model the same class of responses that can be mo...