Meanings of maximum likelihood estimation in inglês

Heritability estimates were derived from variance decomposition models using maximum likelihood estimation.

This procedure requires constrained maximum likelihood estimation via isotonic regression.

Frequentist maximum likelihood estimation or Bayesian inference can then be applied for parameter estimation.

General linear models with restricted maximum likelihood estimation and robust sandwich variance estimators were implemented.

Indirect effects were estimated using structural equation models with maximum likelihood estimation and bootstrapped confidence intervals.

The new Monte Carlo methods permit approximate maximum likelihood estimation in the presence of such complexity.

In this context it is possible to construct a simple and effective algorithm for rapid maximum likelihood estimation of all propensities.

A random effects model with restricted maximum likelihood estimation was constructed for each outcome, and the slope was the parameter of interest.

This article presents a new method for maximum likelihood estimation of logistic regression models with incomplete covariate data where auxiliary information is available.

This article compares the performance of a maximum likelihood estimation of the mixed effects logistic regression model with equal and unequal cluster sizes.

We considered both Gaussian and Poisson models for the noise in combination with Tikhonov regularization, entropy regularization, Good's roughness and without regularization ( maximum likelihood estimation).