Maximum likelihood estimation of parameters in the inverse gaussian distribution with unknown origin. Technometrics, 23, pp. 257-263.Cheng RCH, Amin NAK. Maximum likelihood estimation of parameters in the inverse Gaussian distribution, with unknown origin. Technometrics. 1981;23(3):257-63....
signal detection theory, maximum-likelihood estimation of parameters & determination of confidence intervalsProcedures have been developed for obtaining maximum-likelihood estimates of the parameters of the Thurstonian model for the method of successive intervals. The signal-detection model for rating-method...
Maximum likelihood estimationMethod of momentsMultivariate beta distributionTrigamma functiondoi:10.2307/2347605A. NarayananJohn Wiley & Sons, LtdJournal of the Royal Statistical Society: Series C (Applied Statistics)Narayanan A (1991) Algorithm AS 266: maximum likelihood estimation of the parameters of ...
The estimation of a parameter lying in a subset of a set of possible parameters is considered. This subset is the null space of a well-behaved function and the estimator considered lies in the subset and is a solution of likelihood equations containing a Lagrangian multiplier. It is proved th...
Possible application of the results obtained to the problem of unfolding histograms is briefly discussed.doi:10.1007/BF02613893Zbigniew SzkutnikPhysica-VerlagMetrikaSzkutnik Z (1996) Quasi maximum likelihood estimation of parameters in a multivariate Poisson process. Metrika 43:1–16 MATH MathSciNet...
One of the most important parameters in population genetics is theta = 4N(e)mu where N(e) is the effective population size and mu is the rate of mutation per gene per generation. We study two related problems, using the maximum likelihood method and the theory of coalescence. One problem ...
Estimation of the parameters of a population from a multi-censored sample An extension of the censorship procedure to another general type is considered for estimation by the method of maximum likelihood;The non-parametric estimate of the probability of surviving (quantiles) is obtained, and a gener...
Linear regression - Maximum Likelihood Estimationby Marco Taboga, PhDThis lecture shows how to perform maximum likelihood estimation of the parameters of a linear regression model whose error terms are normally distributed conditional on the regressors. ...
The sensitivity of marginal maximum likelihood estimation of item and ability (theta) parameters was examined when prior ability distributions were not mat... Seong,T.-J. - 《Applied Psychological Measurement》 被引量: 82发表: 1990年 MML estimation of the parameters of the spherical fisher distrib...
Thus, the result in Rothenberg (1971) does not apply but the parameters may still be identifiable in all cases. We consider the case that the information matrix of the likelihood function is singular at θ 0 , with a subvector θ 20 of θ 0 being zero. We propose to estimate θ = (...