A new class of robust regression estimators is proposed that forms an alternative to traditional robust one-step estimators and that achieves the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$\sqrt{n}$</EquationSource> </InlineEquation> rate of convergence irrespective of the initial estimator under a wide range of distributional assumptions. The proposed reweighted least...</equationsource></inlineequation>

We propose a U-statistics-based test for null variance components in linear mixed models and obtain its asymptotic distribution (for increasing number of units) under mild regularity conditions that include only the existence of the second moment for the random effects and of the fourth moment...

In this paper a k-nearest neighbor type estimator of the marginal density function for a random field which evolves with time is considered. Considering dependence, the consistency and asymptotic distribution are studied for the stationary and nonstationary cases. In particular, the parametric...

This survey intends to collect the developments on Goodness-of-Fit for regression models during the last 20 years, from the very first origins with the proposals based on the idea of the tests for density and distribution, until the most recent advances for complex data and models. Far from...

This paper considers optimal experimental designs for models with correlated observations through a covariance function depending on the magnitude of the responses. This suggests the use of stochastic processes whose covariance structure is a function of the mean. Covariance functions must be...

This paper addresses the task of eliciting an informative prior distribution for multinomial models. We first introduce a method of eliciting univariate beta distributions for the probability of each category, conditional on the probabilities of other categories. Two different forms of...

In this paper we discuss estimation and diagnostic procedures in semiparametric additive models with symmetric errors in order to permit distributions with heavier and lighter tails than the normal ones, such as Student-t, Pearson VII, power exponential, logistics I and II, and contaminated...

We present the basic distribution theory of δ-record values, R <Subscript> n,δ </Subscript>, δ≤0, from a sequence of independent and identically distributed random variables from an absolutely continuous parent. We obtain recurrent formulas for the density function of R <Subscript> n,δ </Subscript> and a representation for this random...</subscript></subscript>

Discussing the paper “Model-free model-fitting and predictive distributions” by Politis (<CitationRef CitationID="CR13">2013</CitationRef>), we propose to extend this procedure to semiparametric and parametric mixed effects models (MEM) as in practice, these are probably the most popular ones for prediction. Specifically, combining...</citationref>

It is well known that the traditional estimated risk for the Markowitz mean-variance optimization had been demonstrated to seriously depart from its theoretic optimal risk due to accumulation of input estimation errors. Fan et al. (in J. Am. Stat. Assoc. 107:592–606, <CitationRef CitationID="CR4">2012a</CitationRef>) addressed the...</citationref>