We present a methodology for learning spline-based probabilistic models for sets of contours, proposing a new Monte Carlo variant of the EM algorithm to estimate the parameters of...
We estimate the variance parameter of a stationary simulation-generated process using “folded” versions of standardized time series area estimators. We formulate improved vari...
Claudia Antonini, Christos Alexopoulos, David Gold...
Existing approaches to timing analysis under uncertainty are based on restrictive assumptions. Statistical STA techniques assume that the full probabilistic distribution of parame...
Wei-Shen Wang, Vladik Kreinovich, Michael Orshansk...
In this article we consider the statistical inferences of the unknown parameters of a Weibull distribution when the data are Type-I censored. It is well known that the maximum lik...
—Variations of process parameters have an important impact on reliability and yield in deep sub micron IC technologies. One methodology to estimate the influence of these effects...