This paper introduces the class of seasonal specific structural time series models, according to which each season follows specific dynamics, but is also tied to the others by a common random effects. This results in a dynamic variance components model that can account for some kind of periodic behaviour, such as periodic heteroscedasticity, and is tailored to deal with situations when one or a...

In many applications, the duration of an uninterrupted measurement of a time series is limited. However, it is often possible to obtain several separate segments of data. The estimation of an autoregressive model from this type of data is discussed. A straightforward approach is to take the average of models estimated from each segment separately. In this way, the variance of the estimated para...

This paper presents an econometric model that combines macroeconomic time series data with historical series relating to political instability in Israel during the Intifada period, in order to provide a conservative estimate of the extent to which variations in economic performance over time have a political explanation. Political instability is found to have a substantial effect on the cyclica...

The few existing empirical studies of U.S.-Japan trade agreements have relied primarily on descriptive statistics or univariate time series methods. We conduct a more powerful test by evaluating agreements in the context of well-specified econometric models. Consistent with trade theory, import demand is modeled as a cointegrating relationship with income and relative price variables, where a t...

Policy makers and managers sometimes assess the share of research produced by a group (country, department, institution). This takes the form of the percentage of publications in a journal, field or broad area that has been published by the group. This quantity is affected by essentially random influences that obscure underlying changes over time and differences between groups. A model of resea...

This paper is a selective review of the development of the threshold model in time series analysis over the past 30 years or so. First, it re-visits the motivation of the model. Next, it describes the various expressions of the model, highlighting the principle underlying them and the main probabilistic and statistical properties. Finally, after listing some of the recent offsprings of the thre...

The finite-lattice method of series expansions has been combined with a new extrapolation procedure to extend the low-temperature series for the specific heat, spontaneous magnetisation and susceptibility of the spin-1 Ising model on the square lattice. The extended series were derived by directly calculating the series to order 99 (in the variable u = exp[−J/k B T ]) and using the new extrapol...

Background and Objectives: Efficient cost management in hospitals’ pharmaceutical inventories have the potential to remarkably contribute to optimization of overall hospital expenditures. To this end, reliable forecasting models for accurate prediction of future pharmaceutical demands are instrumental. While the linear methods are frequently used for forecasting purposes chiefly due to their si...

The structure of a tness landscape is still an ill de ned concept This paper introduces a statis tical tness landscape analysis that can be used on a multitude of tness landscapes The result of this analysis is a statistical model that together with some statistics denoting the explanatory and predictive value of this model can serve as a measure for the structure of the landscape The analysis ...