In a recent article, Bai and Perron (2003, Journal of Applied Econometrics) present a comprehensive discussion of computational aspects of multiple structural change models along with several empirical examples. Here, we report on the results of a replication study using the R statistical...

The article shows by various examples how consumers of statistical information may be confused when this information is presented in terms of conditional probabilities. It also shows how this confusion helps others to lie with statistics, and it suggests how either confusion or lies can be...

In this paper we investigate several tests for the hypothesis of a parametric form of the error distribution in the common linear and nonparametric regression model, which are based on empirical processes of residuals. It is well known that tests in this context are not asymptotically...

In this paper we compare data from BTA deep-hole drilling experiments conducted according to an experimental design, which had to be repeated due to the development of spiralling in all experiments in the first repetition. We compare the time series of the drilling torque and the bending moment...

In dose response studies, the dose range is often restricted due to concerns over drug toxicity and/or efficacy. We present restricted and unrestricted interval locally optimal designs with respect to a very general class of optimality criteria for estimating the underlying dose response curve....

Potentially adverse human and environmental effects due to hormone mimicry of environmental estrogens are a matter of current concern. Environmental estrogens belong to the socalled endocrine active compounds (EAC) and may alter signalling processes of the endocrine system leading to a broad...

A monotone estimate of the conditional variance function in a heteroscedastic, nonpara- metric regression model is proposed. The method is based on the application of a kernel density estimate to an unconstrained estimate of the variance function and yields an esti- mate of the inverse variance...