This paper employs concepts from information theory to choosing the dimension of a data set. We propose a relative information measure connected to Kullback-Leibler numbers. By ordering the series of the data set according to the measure, we are able to obtain a subset of a data set that is most...

Factor models can cope with many variables without running into scarce degrees of freedom problems often faced in a regression-based analysis. In this article we review recent work on dynamic factor models that have become popular in macroeconomic policy analysis and forecasting. By means of an...

This paper attempts to find the possibilities of simplifying a multiple time series. We consider a dynamic factor model, Zt=i=1minfiXt-i+Gt, where Zt is a k-dimensional Gaussian stationary time series, Xt is an unobservable r-dimensional factor series (Kr) and t is a (K-r)-dimensional white...

This paper employs concepts from information to choosing the dimension of a data set. We calculate relative measures of information in the data in terms of eigenvalues and derive criteria to determine the ‘optimal’ size of the data set, in particular whether an extra variable adds...