Total Error in a Plug-in Estimator of Level Sets

Given a probability density f on R^d, the minimum volume set of probability content á can be estimated by the level set of the same probability content corresponding to a kernel estimator of f. We obtain convergence rates for this plug-in estimator with respect to a measure-based distance between sets. This distance has a straightforward interpretation in the context of cluster analysis.

MEAN SQUARED ERRORS OF SMALL AREA ESTIMATORS UNDER A UNIT-LEVEL MULTIVARIATE MODEL

This work deals with estimating the vector of means of characteristics of small areas. In this context, a unit level multivariate model with correlated sampling errors is considered. An approximation is obtained for the mean squared and cross product errors of the empirical best linear unbiased predictors of the means. This approach has been implemented on a Monte Carlo study using economic data observed for a sample of Australian farms.

Correction to "Leverage and volatility feedback effects in high-frequency data" [J. Financial Econometrics 4 (2006) 353--384]

Bollerslev et al. (2006) study the cross-covariances for squared returns under the Heston (1993) stochastic volatility model. In order to obtain these cross-covariances the authors use an incorrect expression for the distribution of the squared returns. Here we will obtain the correct distribution of the squared returns and check that, under this new distribution, the result in Appendix A.2 in Bollerslev et al. (2006) still holds.Comment: 3 page