20 search results - page 2 / 4 » Parametric Sensitivity Analysis Using Large-Sample Approxima... |
CSDA
2010
13 years 7 months ago
2010
A two component parametric mixture is proposed to model survival after an invasive treatment, when patients may experience different hazards regimes: a risk of early mortality dir...
ML
2012
ACM
12 years 3 months ago
2012
ACM
Bayesian learning, widely used in many applied data-modeling problems, is often accomplished with approximation schemes because it requires intractable computation of the posterio...
NIPS
2007
13 years 9 months ago
2007
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
IJCAI
1993
13 years 8 months ago
1993
Uncertainty processing methods are analysed from the viewpoint of their sensitivity to small variations of certainty factors. The analysis makes use of the algebraic theory which ...
BMCBI
2010
13 years 7 months ago
2010
Background: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractab...