This paper presents a regression procedure for inhomogeneous data characterized by varying variance, skewness and kurtosis or by an unequal amount of data over the estimation domain. The concept is based first on the estimation of the densities of an observed variable for given values of...

Recently, the OMX Nordic Exchange reduced the exchange fee for trading the OMXS 30 index futures with more than 22%. The reduction in exchange fees provides this study with a unique opportunity to investigate the effects of a change in fixed transaction costs on futures market liquidity, trading...

Examples of real data for which various robust methods give rather different estimates of regression model are presented and the reasons of the phenomenon are outlined. Two examples of invented data which enlighten for which kind of data we may expect the diversity of estimates (yielded even -...

A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to...

The objective of this paper is to compare the performance of two predictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled....

Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many...

Quantile regression (QR) is a principal regression method for analyzing the impact of covariates on outcomes. The impact is described by the conditional quantile function and its functionals. In this paper we develop the nonparametric QR series framework, covering many regressors as a special...

Motivated by the fact that a linear speci fication in a quantile regression setting is unable to describe the non-linear relations among economic variables, as documented in the empirical econometrics literature, we are the first to formulate and analyze a multiple threshold quantile regression...