Примеры использования Maximum likelihood на Английском языке и их переводы на Русский язык
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They are usually estimated using maximum likelihood.
The maximum likelihood estimators estimate the parameters using a maximum likelihood approach.
Parameters are determined using the maximum likelihood method.
The maximum likelihood principle in assumption of phase errors normal probability distribution in measuring channel is used.
The logit model is estimated using the maximum likelihood approach.
Parameter estimation via maximum likelihood and the method of moments has been studied.
That problem never arises in the method of maximum likelihood.
Separately, we focused on the maximum likelihood method, analysis of nonlinear models and discrete variables, logit, probit and ordered probit models.
And EM algorithm estimates the parameters of PISA model with maximum likelihood approach.
An example is the Shtarkov normalized maximum likelihood code, which plays a central role in current MDL theory, but has no equivalent in Bayesian inference.
Th e data from the study on temperamental traits was analyzed by model fi tting using the method of maximum likelihood carried out by LISREL 8.03.
The Baum-Welch algorithm uses the well known EM algorithm to find the maximum likelihood estimate of the parameters of a hidden Markov model given a set of observed feature vectors.
This lagged dependent variable is endogenous, andestimation requires either two-stage least squares or maximum likelihood methods.
Estimation can either be by maximum likelihood or Bayesian.
SEM was estimated in two alternative ways: first, by 3-step least squares method(3SLS), second,by full information maximum likelihood method FIML.
This code could be the normalized maximum likelihood code or a Bayesian code.
If we assume, that the value of S>0 is operation failure, then coefficients α andβ may be estimated on the basis of the sample data using the method of maximum likelihood.
After about a week of struggling, I chose"Advanced Topics in Maximum Likelihood Estimation" and"Complex System in Social Sciences.
Mechanistic models describe all substitutions as a function of a number of parameters which are estimated for every data set analyzed,preferably using maximum likelihood.
Keywords: Satellite altimeter, echo-signal,power profile, maximum likelihood estimate, time discriminator, modulation mode.
After receiving a grant to travel to school ICPSR I initially signed up to take the courses"Regression III" and"Advanced Topics in Maximum Likelihood Estimation.
Phylogenic analysis was carried out using MEGA 5.2, Maximum Likelihood statistical analysis and Kimura bootstrap level 1,000.
A maximum likelihood analysis of four genes by computational phylogenetics indicated that M. proboscideus and M. flavicaudatus are sister species, with M. micus being less closely related.
The'best'(in the sense that it has a minimax optimality property)are the normalized maximum likelihood(NML) or Shtarkov codes.
If instead of the Bayes factor integral,the likelihood corresponding to the maximum likelihood estimate of the parameter for each statistical model is used, then the test becomes a classical likelihood-ratio test.
The Italian presentation proposed a method for estimating a global measure of the re-identification risk in microdata that makes use of the concept of smoothing in contingency tables and penalized maximum likelihood approach.
As a result, the standard results for consistency andasymptotic normality of maximum likelihood estimates of β{\displaystyle\beta} only apply when β≥ 2{\displaystyle\textstyle\beta\geq 2.
Maximum likelihood robust algorithm for tonal source bearing estimation is designed in the presence of smooth field fluctuations on the aperture of linear antenna array; the algorithm is invariant with respect to coefficients determined field distortion.
We do not employ here Mundlak's approach because of technical difficulties of such estimation by FIML(Full Information Maximum Likelihood) that is very demanding to the system specification.
It features a variety of estimators such as least-squares and maximum likelihood; several time series methods such as ARIMA and GARCH; limited dependent variables such as logit, probit and tobit; and a powerful scripting language.