Results 1  10
of
1,214,646
Maximum likelihood from incomplete data via the EM algorithm
 JOURNAL OF THE ROYAL STATISTICAL SOCIETY, SERIES B
, 1977
"... A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value situat ..."
Abstract

Cited by 11807 (17 self)
 Add to MetaCart
A broadly applicable algorithm for computing maximum likelihood estimates from incomplete data is presented at various levels of generality. Theory showing the monotone behaviour of the likelihood and convergence of the algorithm is derived. Many examples are sketched, including missing value
Exact maximum likelihood estimation for word mixtures
 In Text Learning Workshop in International Conference on Machine Learning (ICML2002
, 2002
"... The mixture model for generating document is a generative language model used in information retrieval. While using this model, there are situations that we need to find the maximum likelihood estimation of the density of one multinomial, given fixed mixture weight and the densities of the other mul ..."
Abstract

Cited by 19 (2 self)
 Add to MetaCart
The mixture model for generating document is a generative language model used in information retrieval. While using this model, there are situations that we need to find the maximum likelihood estimation of the density of one multinomial, given fixed mixture weight and the densities of the other
Exact Maximum Likelihood Estimation of ObservationDriven Econometric Models
"... : The possibility of exact maximum likelihood estimation of many observationdriven models remains an open question. Often only approximate maximum likelihood estimation is attempted, because the unconditional density needed for exact estimation is not known in closed form. Using simulation and nonp ..."
Abstract

Cited by 5 (0 self)
 Add to MetaCart
: The possibility of exact maximum likelihood estimation of many observationdriven models remains an open question. Often only approximate maximum likelihood estimation is attempted, because the unconditional density needed for exact estimation is not known in closed form. Using simulation
Exact Maximum Likelihood Estimation for NonGaussian Noninvertible Moving Averages
, 2005
"... A procedure for solving exact maximum likelihood estimation (MLE) is proposed for noninvertible nonGaussian MA processes. By augmenting certain latent variables, the exact likelihood of all relevant innovations can be expressed explicitly according to a set of recursions (Breidt and Hsu, 2005). Th ..."
Abstract
 Add to MetaCart
A procedure for solving exact maximum likelihood estimation (MLE) is proposed for noninvertible nonGaussian MA processes. By augmenting certain latent variables, the exact likelihood of all relevant innovations can be expressed explicitly according to a set of recursions (Breidt and Hsu, 2005
"Exact Maximum Likelihood Estimation of ARCH Models. " Helpful
, 1996
"... Abstract: The possibility of exact maximum likelihood estimation of many observationdriven models remains an open question. Often only approximate maximum likelihood estimation is attempted, because the unconditional density needed for exact estimation is not known in closed form. Using simulation ..."
Abstract
 Add to MetaCart
Abstract: The possibility of exact maximum likelihood estimation of many observationdriven models remains an open question. Often only approximate maximum likelihood estimation is attempted, because the unconditional density needed for exact estimation is not known in closed form. Using
Fast Exact Maximum Likelihood Estimation for Mixture of Language Models ABSTRACT
"... A common language modeling approach assumes the data D is generated from a mixture of several language models. EM algorithm is usually used to find the maximum likelihood estimation of one unknown mixture component, given the mixture weights and the other language models. In this paper, we provide a ..."
Abstract

Cited by 1 (0 self)
 Add to MetaCart
A common language modeling approach assumes the data D is generated from a mixture of several language models. EM algorithm is usually used to find the maximum likelihood estimation of one unknown mixture component, given the mixture weights and the other language models. In this paper, we provide
EXACT MAXIMUM LIKELIHOOD ESTIMATOR FOR DRIFT FRACTIONAL BROWNIAN MOTION AT DISCRETE OBSERVATION
, 904
"... This paper deals with the problems of consistence and strong consistence of the maximum likelihood estimators of the mean and variance of the drift fractional Brownian motions observed at discrete time instants. A central limit theorem for these estimators is also obtained by using the Malliavin cal ..."
Abstract

Cited by 4 (0 self)
 Add to MetaCart
This paper deals with the problems of consistence and strong consistence of the maximum likelihood estimators of the mean and variance of the drift fractional Brownian motions observed at discrete time instants. A central limit theorem for these estimators is also obtained by using the Malliavin
Poster Fast Exact Maximum Likelihood Estimation for Mixture of Language Models
"... A common language modeling approach assumes the data D is generated from a mixture of several language models. EM algorithm is usually used to find the maximum likelihood estimation of one unknown mixture component, given the mixture weights and the other language models. In this paper, we provide a ..."
Abstract
 Add to MetaCart
A common language modeling approach assumes the data D is generated from a mixture of several language models. EM algorithm is usually used to find the maximum likelihood estimation of one unknown mixture component, given the mixture weights and the other language models. In this paper, we provide
Exact Maximum Likelihood estimator for the BLGARCH model under elliptical distributed
, 2009
"... innovations ⋆ ..."
Exact Maximum Likelihood Estimation of Structured or Unit Root Multivariate Time Series Models ∗
, 2004
"... ∗ The authors thank Saïd Nsiri for helpful comments. This work has been partly funded by the cooperation between ..."
Abstract

Cited by 7 (1 self)
 Add to MetaCart
∗ The authors thank Saïd Nsiri for helpful comments. This work has been partly funded by the cooperation between
Results 1  10
of
1,214,646