We study locally D-optimal designs for some exponential models that are frequently used in the biological sciences. The model can be written as an algebraic sum of two or three exponential terms. We show that approximate locally D-optimal designs are supported at a minimal number of points and...

In this note we consider several goodness-of-fit tests for model specification in non- parametric regression models which are based on kernel methods. In order to circumvent the problem of choosing a bandwidth for the corresponding test statistic we propose to consider the statistics as...

The problem of constructing standardized maximin D-optimal designs for weighted polynomial regression models is addressed. In particular it is shown that, by following the broad approach to the construction of maximin designs introduced recently by Dette, Haines and Imhof (2003), such designs...

In this paper we investigate locally E- and c-optimal designs for exponential regression models of the form _k i=1 ai exp(??ix). We establish a numerical method for the construction of efficient and locally optimal designs, which is based on two results. First we consider the limit ?i ? ? and...

Classical regression analysis is usually performed in two steps. In a first step an appropriate model is identified to describe the data generating process and in a second step statistical inference is performed in the identified model. An intuitively appealing approach to the design of...

The forecasting of time series in goods management systems causes various problems that we identify and indicate possible solutions. The implementation of auxiliary information like promotional activities or calendar effects in forecasts using ARMA models and exponential smoothing methods may be...

In this paper sequential monitoring schemes to detect nonparametric drifts are studied for the random walk case. The procedure is based on a kernel smoother. As a by-product we obtain the asymptotics of the Nadaraya-Watson estimator and its associated sequential partial sum process under...

If we are given a time series of economic data, a basic question is whether the series is stationary or a random walk, i.e., has a unit root. Whereas the problem to test the unit root null hypothesis against the alternative of stationarity is well studied in the context of classic hypothesis...

Testing for unit roots has been among the most heavily researched topics in Econometrics for the last quarter of a century. Much less researched is the equally important issue of the appropriate transformation if any of the variable of interest which should preceed any such testing. In...

We derive the probability limit of the standard Dickey-Fuller-test in the context of an exponential random walk. This result might be useful in interpreting tests for unit roots when the test is inadvertantly applied to the levels of the data when the true random walk is in the logs.