Maximum likelihood estimationTime series analysisEigenvaluesRegression analysisNonlinear analysisRecently Kundu(1993a) has proposed a non-linear eigenvalue method for finding the maximum likelihood estimators (MLE) of the parameters of undamped exponential signals.It is known to perform better than the ...
We study constrained maximum likelihood estimation and tests under the logistic regression model based on case-control data. Our approach is based on the semiparametric profile log likelihood function under a two-sample semiparametric model, which is equivalent to the assumed logistic regression model. ...
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This paper describes a SQP-type algorithm for solving a constrained maximum likelihood estimation problem that incorporates a number of novel features. We call it MLESOL. MLESOL maintains the use of an estimate of the Fisher information matrix to the Hessian of the negative log-likelihood but als...
Dykstra (1982) also considered constrained nonparametric maximum likelihood estimation for such problems, however, as we show, Dykstra's method has an error and does not always give the C-NPMLE. We corrected this error and simulation shows improvement in efficiency compared to Dykstra's estimator....
A numerical maximum likelihood (ML) estimation procedure is developed for the constrained parameters of multinomial distributions. The main difficulty involved in computing the likelihood function is the precise and fast determination of the multinomial coefficients. For this the coefficients are rewritten ...
SubjectRe: st: constrained parameter in maximum likelihood estimation DateThu, 25 Sep 2003 01:22:39 +0800 Thursday, September 25, 2003, 12:44:03 AM, Jun Xu wrote: > Stata Listers: > I have a programming question using ml command: how to contrain some > parameter to be estimated withi...
In unconstrained maximum a posteriori (MAP) and maximum likelihood estimation, the inverse of minus the merit-function Hessian matrix is an approximation of the estimate covariance matrix. In the Bayesian context of MAP estimation, it is the covariance of a normal approximation of the posterior ...
We discuss in this paper asymptotics of locally optimal solutions of maximum likelihood and, more generally, M-estimation procedures in cases where the tru... A Shapiro - 《Annals of Statistics》 被引量: 0发表: 2000年 On constrained and regularized high-dimensional regression High-dimensional feat...
maximum likelihood estimationregression analysiszoology/ objective Bayesian analysisexponential regression modelconstrained parameteranimal digestibilitydegraded foodrandom variableparameter estimationIn animal digestibility the proportion of degraded food along the time has usually been modeled as a normal random ...