The objective of change-point detection is to discover abrupt property changes lying behind time-series data. In this paper, we present a novel statistical change-point detection algorithm based on non-parametric divergence estimation between time-series samples from two retrospective segments. Our method uses the relative Pearson divergence as a divergence measure, and it is accurately and eff...

This paper investigates a change-point estimation problem in the context of high-dimensional Markov random field models. Change-points represent a key feature in many dynamically evolving network structures. The change-point estimate is obtained by maximizing a profile penalized pseudo-likelihood function under a sparsity assumption. We also derive a tight bound for the estimate, up to a logari...

♦ parameter space-Ω = {all θ} ♦ estimator-a random variable (or vector) ♦ estimate-a value (vector) derived from a realization ♦ (log)-likelihood function-n i=1 f (x i ; θ). ♦ maximum likelihood estimator (estimate)[mle]) is called an unbiased estimator of θ. Otherwise, it is said to be biased. ♦ parameter estimation by method of moments. Example 1: mle for the mean and variance of a random sam...

In survival analysis or reliability and maintenance studies, hazard-rate function plays an important role, since it describes the instantaneous failure probability given that the individual survived or the item has not failed up to that instance. Sudden changes in the hazard function may occur due to overhauls, treatment effects or maintenance activities. A problem of statistical interest is th...

Some asymptotic properties of point estimation with n-dimensional fuzzy data with respect to a special L2-metric ρ are investigated in this paper. It is shown that the collection of all n-dimensional fuzzy data endowed with the ρ-metric is a complete and separable space. Some criterions for point estimation in such fuzzy environments are proposed and the sample mean and variance and covariance ...

This paper proposes a technique that estimates the locations along the string of the plucking event and the magnetic pickup of an electric guitar based on the autocorrelation of the spectral peaks. To improve accuracy, a method is introduced to flatten the spectrum before applying the autocorrelation function to the spectral peaks. The minimum mean squared error between the autocorrelation of t...

This vignette demonstrates the use of the R package laeken for standard point estimation of indicators on social exclusion and poverty according to the definitions by Eurostat. The package contains synthetically generated data for the European Union Statistics on Income and Living Conditions (EU-SILC), which is used in the code examples throughout the paper. Furthermore, the basic object-orient...

Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by in...