17 search results - page 1 / 4 » Nonlinear random effects mixture models: Maximum likelihood ... |
CSDA
2007
13 years 4 months ago
2007
Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
NIPS
1998
13 years 6 months ago
1998
We present the CEM (Conditional Expectation Maximization) algorithm as an extension of the EM (Expectation Maximization) algorithm to conditional density estimation under missing ...
ICIP
2001
IEEE
14 years 6 months ago
2001
IEEE
The HMM (Hidden Markov Model) is a probabilistic model of the joint probability of a collection of random variables with both observations and states. The GMM (Gaussian Mixture Mo...
IPM
2008
13 years 4 months ago
2008
Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
ICML
2008
IEEE
14 years 5 months ago
2008
IEEE
EM algorithm is a very popular iteration-based method to estimate the parameters of Gaussian Mixture Model from a large observation set. However, in most cases, EM algorithm is no...