We consider the analysis of clustered data using linear mixed effects models and generalized estimating equations, where covariates can be decomposed into betweenand within-cluster components. Under the false assumption of equal betweenand within-cluster covariate effects, we simultaneously study the asymptotic behavior of the estimators for regression coefficients, intra-cluster correlation an...

We present a general theory of estimation of analysis error covariances based on 9 cross-validation as well as a geometric interpretation of the method. In particular we use the variance 10 of passive observation–minus-analysis residuals and show that the true analysis error variance can be 11 estimated, without relying on the optimality assumption. This approach is used to obtain near 12 optim...

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier and we propose an improved estimator of the population frontier. In addition, we provide the exact distribu...

SUMMARY Using replicated human serum samples, we applied an error model for proteomic differential expression profiling for a high-resolution liquid chromatography-mass spectrometry (LC-MS) platform. The detailed noise analysis presented here uses an experimental design that separates variance caused by sample preparation from variance due to analytical equipment. An analytic approach based on ...

This study used Monte Carlo simulation to examine the increase in accuracy resulting from 2 statistical refinements of the interactive Schmidt-Hunter procedures for meta-analysis: the use of the mean correlation instead of individual correlations in the estimation of sampling error variance, and a procedure that takes into account the nonlinear nature of the range-restriction correction. In all...

Spiine, periodic spline and spherical harmonic maximum reach estimation procedures are compared and evaluated based on ease of usage, estimation error and bias. The comparison indicates that each method provides comparable estimates based on percent variance accounted for (Rz) and standard error. Spherical harmonics, however, are less biased and provide accurate estimates of the maximum reach s...

The development of communications and telecommunications infrastructure, followed by the extension of a new generation of smart distribution grids, has brought real-time control of distribution systems to electrical industry professionals’ attention. Also, the increasing use of distributed generation (DG) resources and the need for participation in the system voltage control, which is possible ...

in this article, the discrete time state space model with first-order autoregressive dependent process noise is considered and the recursive method for filtering, prediction and smoothing of the hidden state from the noisy observation is designed. the explicit solution is obtained for the hidden state estimation problem. finally, in a simulation study, the performance of the designed method ...