We explore different approaches for performing hypothesis tests on the shape of a mean function by developing general methodologies both, for the often assumed, i.i.d. error struc...
The assessment of the influence of individual observations on the outcome of the analysis by perturbation has received a lot of attention for situations in which the observations ...
Emerging patterns represent a class of interaction structures which has been recently proposed as a tool in data mining. In this paper, a new and more general definition refering ...
A new method is proposed to estimate the nonlinear functions in an additive regression model. Usually, these functions are estimated by penalized least squares, penalizing the cur...
The Hurst parameter H characterizes the degree of long-range dependence (and asymptotic selfsimilarity) in stationary time series. Many methods have been developed for the estimat...
Stilian Stoev, Murad S. Taqqu, Cheolwoo Park, Geor...
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...
A possible approach to bandwidth selection for difference-based variance estimators in the nonparametric regression is proposed. The approach is based on the crossvalidation-type ...
The comparison of the accuracy of two binary diagnostic tests has traditionally required knowledge of the real state of the disease in all of the patients in the sample via the ap...