Estimation of Error Variance in One-Way Random Model.
Estimation of log-linear-binomial distribution with applications.
Estimation of parameters in a network reliability model with spatial dependence
An iterative method based on a fixed-point property is proposed for finding maximum likelihood estimators for parameters in a model of network reliability with spatial dependence. The method is shown to converge at a geometric rate under natural conditions on data.
Estimation of parameters in a network reliability model with spatial dependence
An iterative method based on a fixed-point property is proposed for finding maximum likelihood estimators for parameters in a model of network reliability with spatial dependence. The method is shown to converge at a geometric rate under natural conditions on data.
Estimation of parameters in exponential autoregressive models.
This paper discusses the estimation of parameters in second order exponential autoregressive models.
Estimation of parameters of mean and variance in two-stage linear models
The paper deals with the estimation of unknown vector parameter of mean and scalar parameters of variance as well in two-stage linear model, which is a special type of mixed linear model. The necessary and sufficient condition for the existence of uniformly best unbiased estimator of parameter of means is given. The explicite formulas for these estimators and for the estimators of the parameters of variance as well are derived.
Estimation of parameters of RCA with exponential marginals.
Estimation of polynomials in the regression model
Let be an -dimensional random vector which is distributed. A minimum variance unbiased estimator is given for provided is an unbiasedly estimable functional of an unknown -dimensional parameter .
Estimation of P{Y
Estimation of reliability in the exponential case (I)
Estimation of reliability in the exponential case (II)
Estimation of Symmetrie Functions of a Finite Population.
Estimation of the first order parameters in the twoepoch linear model
The linear regression model, where the mean value parameters are divided into stable and nonstable part in each of both epochs of measurement, is considered in this paper. Then, equivalent formulas of the best linear unbiased estimators of this parameters in both epochs using partitioned matrix inverse are derived.
Estimation of the generalized variance in a bivariate normal distribution from an incomplete sample
The aim of the paper is estimation of the generalized variance of a bivariate normal distribution in the case of a sample with missing observations. The estimator based on all available observations is compared with the estimator based only on complete pairs of observations.
Estimation of the Parameter of the Inverse Gaussian Distribution from Generalised Censored Samples.
Estimation of the parameters of Gumbel and Burr distributions in terms of kth record values
The minimum variance linear unbiased estimators (MVLUE), the best linear invariant estimators (BLIE) and the maximum likelihood estimators (MLE) based on m selected kth record values are presented for the parameters of the Gumbel and Burr distributions.
Estimation of the parameters of the mixture k ≥ 2 of logarithmic-normal distributions.
In the mixture k ≥ 2 of logarithmic-normal distributions, with density function (1), the parameters μ1, ..., μk satisfying conditions (2) and the parameters p1, ..., pk satisfying conditions (3) are unknown. Using moments of orders r = -k, -k+1, ..., 0, 1, ..., k-1 we get a system of 2k equations (8), an equivalent of matrix equation (10). The equation (13) has exactly one solution with regard to A. If in the equation (13) we substitute the unbiased and consistent estimators D'r for the coefficients...
Estimation of the Parameters of the PARETO Distribution
Estimation of the parameters of the reversed generalized logistic distribution with progressive censoring data.
Estimation of the size of a closed population
The problem considered is that of estimation of the size (N) of a closed population under three sampling schemes admitting unbiased estimation of N. It is proved that for each of these schemes, the uniformly minimum variance unbiased estimator (UMVUE) of N is inadmissible under square error loss function. For the first scheme, the UMVUE is also the maximum likelihood estimator (MLE) of N. For the second scheme and a special case of the third, it is shown respectively that an MLE and an estimator...