The aim of the paper is to obtain confidence intervals for the tail index and high quantiles taking into account the optimal rate of convergence of the estimator. The common approach to obtaining confidence intervals presented in the literature is to use the normal distribution approximation at...

The aim of the paper is to obtain confidence intervals for the tail index and high quantiles taking into account the optimal rate of convergence of the estimator. The common approach to obtaining confidence intervals presented in the literature is to use the normal distribution approximation at...

При оценивании производственных функций исследователь сталкивается с рядом проблем, которые в наиболее общем виде можно разделить на две группы: проблемы,...

We show that, in practice, the standard unit root tests, cointegration tests, and similar tests are unreliable. This conclusion is more generally applicable to other regression-based tests. In particular, these tests attempt to solve a problem by creating another problem

This paper studies a balance whose unobservable fulcrum is not necessarily located at the middle of its two pans. It presents three different models, showing how this lack of symmetry modifies the observation, the formalism and the interpretation of such a biased measuring device. It argues that...

We derive new statistical tests for leave-one-out cross-validation of Kriging models. Graphically, we present these tests as scatterplots augmented with confidence intervals. We may wish to avoid extrapolation, which we define as prediction of the output for a point that is a vertex of the...

The paper studies Non-Stationary Dynamic Factor Models such that: (1) the factors F_t are I(1) and singular, i.e. F_t has dimension r and is driven by a q-dimensional white noise, the common shocks, with q r, and (2) the idiosyncratic components are I(1). We show that F_t is driven by r − c...

We study the correct estimation of the true variance of the predictor in stochastic Kriging (SK). First, we obtain macroreplications for a SK metamodel that approximates a single-server simulation model; these macroreplications give independently and identically distributed predictions. This...

Expectile regression produces the best linear unbiased estimator for regression lines other than the mean regression in model designs with asymmetric conditional variance of the error term. In some cases where OLS assumptions are violated, an expectile regression estimator is also the BLUE for...

This article compares two asymmetric Gaussian likelihood models and their corresponding estimators. Recently, there has been confusion in the literature regarding these models and: (1) whether they are the same, or (2) whether both of them can be used to estimate expectiles. After the...