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Estimation of the parameters was based on partial likelihood maximization.
For ln(Y) and associated censored regression model, ordinary least square estimation of the parameters would produce biased estimators.
Maximum likelihood and Bayesian estimation of the parameters are discussed.
The estimation of the parameters of Eq. (6) is obtained using restricted ordinary least squares (OLS).
Estimation of the parameters in the generalized Birnbaum-Saunders distribution will be discussed.
The estimation of the parameters is approached by the method of maximum likelihood.
Estimation of the parameters of the models and applications are also given.
We discuss the maximum likelihood estimation of the parameters of the KGD in subsection 6.1.
Hence, to ignore blotch pixels allows an improved estimation of the parameters in the remaining stages.
Our algorithm consists in an ICE estimation of the parameters θ=(B,η).
This operation allows for a more appropriate estimation of the parameters in the two remaining stages.
More suggestions(13)
test of the parameters
estimation of the measurements
estimation of the variables
estimation of the measures
estimation of the coefficients
estimation of the determinants
assessment of the parameters
prediction of the parameters
data of the parameters
estimation of the scope
estimates of the parameters
estimation of the identified
estimation of the parametric
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