for these constraints yields estimates for the unknown positions of the nodes in the network. Providing that the constraints are tight enough, simulation illustrates that this estimate becomes close to the actual node positions. Additionally, a method for placing rectangular bounds around the possible positions for all

This study compares the out-of-sample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and trade-weighted dollar

, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily and lower frequencies using ARCH and stochastic volatility type models. Most of these studies find highly significant in-sample parameter estimates and pronounced intertemporal

sciences are a biased sample of the studies that are actually carried out (Bakan, 1967; McNemar, 1960; Smart, 1964; Sterling, 1959). The extreme view of this problem, the "file drawer prob-lem, " is that the journals are filled with the 5 % of the studies that show Type I errors, while the file

scientist (see It rapidly became evident, however, that the social perceiver's actual inferential work and decision making looked little like these normative models. Rather, information processing is full of incomplete data gathering, shortcuts, errors, and biases (see At this point, we exchange

consumption tends to vary significantly with the actual computing activity. Effective power provisioning strategies are needed to determine how much computing equipment can be safely and efficiently hosted within a given power budget. In this paper we present the aggregate power usage characteristics of large

that statistical framework is getting more transparent. The subject with statistical emphasis has been evolving, as seen by various excellent books from statistical sides (Banerjee, S., Introduction It is well known that the maximum likelihood (ML) method is a powerful statistical tool in estimation

, if s was sampled from the distribution obtained by following π, then a ∂π(s,a) ∂θ Q π (s, a) would be an unbiased estimate of ∂ρ ∂θ . Of course, Q π (s, a) is also not normally known and must be estimated. One approach is to use the actual returns, corrects for the oversampling of actions preferred by π), which

climate. 9 II. Data Our first objective is to investigate how well the variables identified above explain observed changes in credit spreads. Here, we discuss the data used for estimating both credit spreads and proxies for the explanatory variables. Credit Spreads The corporate bond data are obtained

policy shocks) allows for an empirical investigation of the effects of such shocks and of their contribution to business cycle fluctuations in the euro area. Using the estimated model, the paper also analyses the output (real interest rate) gap, defined as the difference between the actual and model