Quantitative stochastic simulation is an important tool in assessing the performance of complex dynamic systems such as modern communication networks. Because of the proliferation of computers and devices that use and rely on networks such as the internet, assessing the performance of these networks is important to ensure future reliability and service. The current methodology for the analysis ...

Variance estimation for estimators of state, county, and school district quantities derived from the Census 2000 long form are discussed. The variance estimator must account for (1) uncertainty due to imputation, and (2) raking to census population controls. An imputation procedure that imputes more than one value for each missing item using donors that are neighbors is described and the proced...

Scalable Ensemble Learning and Computationally Efficient Variance Estimation

A gene-expression microarray datum is modeled as an exponential expression signal (log-normal distribution) and additive noise. Variance-stabilizing transformation based on this model is useful for improving the uniformity of variance, which is often assumed for conventional statistical analysis methods. However, the existing method of estimating transformation parameters may not be perfect bec...