Minimization of suitable statistical distances (between the data and model densities) is a useful technique in field robust inference. Apart from class ϕ-divergences, Bregman divergence extensively used for this purpose. However, since density must have linear presence term involving both densities structure, several divergences cannot be captured by usual form. We provide an extension consider...

Cost engineers of buying enterprises perform detailed product cost calculations externally manufactured components. The aim these is to determine what a should and support purchasing functions in fact-based negotiations. While have deep knowledge the calculation direct cost, they need supplier´s indirect categories. industrial rent, which expressed annual per m² occupied plant building floor sp...

This paper focuses on semi-parametric estimation of multivariate expectiles for extreme levels risk. Multivariate and their extremes have been the focus plentiful research in recent years. In particular, it has noted that due to difficulty estimating these values elevated risk, an alternative formulation underlying optimization problem would be necessary. However, such a scenario, estimators on...

High-resolution methods are generally defined to be high-performance methods for estimating and/or detecting the desired and/or undesired signal components present in a given set of data. The term “high-resolution” also implies a good ability to resolve very “similar” signal components. One of the most common problems in signal processing is known as frequency estimation. In frequency estimatio...

Estimating the worst-case execution time (WCET) of real-time programs is pivotal in their verification. WCET estimation either yields a numeric value that represents the maximum execution time of the program when executed on a specific hardware platform; or yields a parametric expression in the form of some function of the input which when instantiated with a particular input value, gives a WCE...

This report describes how the choice of kernel affects a non-parametric density estimation. Methods for accurate localisation of peaks in the estimated densities are developed for Gaussian and cos kernels. The accuracy and robustness of the peak localisation methods are studied with respect to noise, number of samples, and interference between peaks. Although the peak localisation is formulated...