This paper first reduces the problem of detecting structural breaks in a random walk to that of finding the best subset of explanatory variables in a regression model and then tailors various subset selection criteria to this specific problem. Of particular interest are those new criteria, which...

A new means of estimating the correlation coefficient for cluster binary data in the regression settings is introduced. The creation of this method is founded upon the violation of Bartlett’s second identity when adopting the binomial distributions to model binary data that are correlated. The...

This paper addresses the retrospective or off-line multiple change-point detection problem. Multiple change-point models are here viewed as latent structure models and the focus is on inference concerning the latent segmentation space. Methods for exploring the space of possible segmentations of...

An essential problem in nonparametric smoothing of noisy data is a proper choice of the bandwidth or window width, which depends on a smoothing parameter <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$k$$</EquationSource> </InlineEquation>. One way to choose <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$k$$</EquationSource> </InlineEquation> based on the data is leave-one-out-cross-validation. The selection of the cross-validation criterion is...</equationsource></inlineequation></equationsource></inlineequation>

In this paper we concentrate on testing for multiple changes in the mean of a series of independent random variables. Suggested method applies a maximum type test statistic. Our primary focus is on an effective calculation of critical values for very large sample sizes comprising (tens of)...

We revisit Hawkins’ (Comput Stat 9(3):233–247, <CitationRef CitationID="CR15">1994</CitationRef>) algorithm for fitting monotonic polynomials and discuss some practical issues that we encountered using this algorithm, for example when fitting high degree polynomials or situations with a sparse design matrix but multiple observations...</citationref>

Assuming a beta prior distribution on the fraction defective, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$p$$</EquationSource> </InlineEquation>, failure-censored sampling plans for Weibull lifetime models using classical (or average) and Bayesian (or posterior) producer’s and consumer’s risks are designed to determine the acceptability of lots of a given product....</equationsource></inlineequation>

We describe a new algorithm for the computation of the score function and observed information in regular vine (R-vine) copula models. R-vine copulas are constructed hierarchically from bivariate copulas as building blocks only, and the algorithm exploits this hierarchical nature for subsequent...

The autoregressive fractionally integrated moving average (ARFIMA) processes are one of the best-known classes of long-memory models. In the package <Emphasis FontCategory="NonProportional">afmtools for <Emphasis FontCategory="NonProportional">R, we have implemented a number of statistical tools for analyzing ARFIMA models. In particular, this package contains functions for...</emphasis></emphasis>

Results on cross category effects obtained by explanatory market basket analyses may be biased as studies typically investigate only a small fraction of the retail assortment (Chib et al. in Advances in econometrics, vol 16. Econometric models in marketing. JAI, Amsterdam, pp 57–92, <CitationRef CitationID="CR11">2002</CitationRef>). We...</citationref>