The paper analyses the leading journals in Neurosciences using quantifiable Research Assessment Measures (RAM), highlights the similarities and differences in alternative RAM, shows that several RAM capture similar performance characteristics of highly cited journals, and shows that some other...

Several methods have recently been proposed in the ultra high frequency financial literature to remove the effects of microstructure noise and to obtain consistent estimates of the integrated volatility (IV) as a measure of ex-post daily volatility. Even bias-corrected and consistent realized...

In this paper we consider the capacitated lot-sizing problem (CLSP) with linear costs. It is known that this problem is NP-hard, but there exist special cases that can be solved in polynomial time. The purpose of this paper is twofold. First, we derive a backward algorithm based on the forward...

In this paper we examine the interaction between data transformation and the empirical evidence obtained when testing for (non-)linearity. For this purpose we examine nonlinear features in 64 monthly and 53 quarterly US macroeconomic variables for a range of Box-Cox data transformations. Our...

In this paper we put forward a new time series model, which describes nonlinearity and seasonality simultaneously. We discuss its representation, estimation of the parameters and inference. This seasonal STAR (SEASTAR) model is examined for its practical usefulness by applying it to 18 quarterly...

Several recent studies show that seasonal variation and cyclical variation in unemployment are correlated. A common finding is that seasonality tends to differ across the business cycle stages of recessions and expansions. Since seasonal adjustment methods assume that the two sources of...

The correct parameter restrictions- less restrictive than commonly thought-of the indirect addilog system (IAS) are derived. Under correct restrictions, the IAS is superior to the linear expenditure system in computable general equilibrium models with data scarcity.

Shortest path problems occupy an important position in Operations Research as well as in Arti¯cial Intelligence. In this paper we study shortest path algorithms that exploit heuristic estimates. The well-known algorithms are put into one framework. Besides we present an interesting...

We propose to estimate the parameters of the Market Share Attraction Model (Cooper & Nakanishi, 1988; Fok & Franses, 2004) in a novel way by using a non-parametric technique for function estimation called Support Vector Regressions (SVR) (Vapnik, 1995; Smola, 1996). Traditionally, the parameters of the...

Scanner data for fast moving consumer goods typically amount to panels of time series where both N and T are large. To reduce the number of parameters and to shrink parameters towards plausible and interpretable values, multi-level models turn out to be useful. Such models contain in the second...