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» Bayesian Parameter Estimation: A Monte Carlo Approach
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ICPR
2010
IEEE
13 years 9 months ago
Learning Probabilistic Models of Contours
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...
Laure Amate, Maria João Rendas
WSC
2007
13 years 9 months ago
Folded standardized time series area variance estimators for simulation
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...
DAC
2006
ACM
14 years 8 months ago
Statistical timing based on incomplete probabilistic descriptions of parameter uncertainty
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...
CSDA
2011
13 years 2 months ago
Inferences on Weibull parameters with conventional type-I censoring
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...
Avijit Joarder, Hare Krishna, Debasis Kundu
DATE
2010
IEEE
171views Hardware» more  DATE 2010»
14 years 13 days ago
Digital statistical analysis using VHDL
—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...
Manfred Dietrich, Uwe Eichler, Joachim Haase