Maximum Likelihood Methods for Fitting the Burr Type XII Distribution to Multiply (Progressively) Censored Life Test Data.
Maximum likelihood principle and -divergence: continuous time observations
The paper investigates the relation between maximum likelihood and minimum -divergence estimates of unknown parameters and studies the asymptotic behaviour of the likelihood ratio maximum. Observations are assumed to be done in the continuous time.
Maximum Probability Estimators in the Case of Exponential Distribution.
Mean-square-error-robustness of linear estimates in the exponential model
Median for metric spaces
We consider a Köthe space of random variables (r.v.) defined on the Lebesgue space ([0,1],B,λ). We show that for any sub-σ-algebra ℱ of B and for all r.v.’s X with values in a separable finitely compact metric space (M,d) such that d(X,x) ∈ for all x ∈ M (we then write X ∈ (M)), there exists a median of X given ℱ, i.e., an ℱ-measurable r.v. Y ∈ (M) such that for all ℱ-measurable Z. We develop the basic theory of these medians, we show the convergence of empirical medians and we give some applications....
Meta-analysis techniques applied in prevalence rate estimation
In some cases, the estimators obtained in compound tests have better features than the traditional ones, obtained from individual tests, cf. Sobel and Elashoff (1975), Garner et al. (1989) and Loyer (1983). The bias, the efficiency and the robustness of these estimators are investigated in several papers, e.g. Chen and Swallow (1990), Hung and Swallow (1999) and Lancaster and Keller-McNulty (1998). Thus, the use of estimators based on compound tests not only allows a substantial saving of...
Minimax estimation of a class of functions of the scale parameter in the gamma and other distributions in the case of truncated parameter space
Minimax estimation of the parameters of the multivariate hypergeometric distribution
Minimax Estimation Under Convex Loss when the Parameter Interval is Bounded.
Minimax Estimators and ...-Minimax Estimators for a Bounded Normal Mean Under the Loss ip(0, d) =I0-dIp
Minimax Estimators for a Bounded Location Parameter.
Minimax Prediction for the Multinomial and Multivariate Hypergeometric Distributions
A problem of minimax prediction for the multinomial and multivariate hypergeometric distribution is considered. A class of minimax predictors is determined for estimating linear combinations of the unknown parameter and the random variable having the multinomial or the multivariate hypergeometric distribution.
Minimax prediction under random sample size
A class of minimax predictors of random variables with multinomial or multivariate hypergeometric distribution is determined in the case when the sample size is assumed to be a random variable with an unknown distribution. It is also proved that the usual predictors, which are minimax when the sample size is fixed, are not minimax, but they remain admissible when the sample size is an ancillary statistic with unknown distribution.
Minimum entropy of error estimate for multi-dimensional parameter and finite-state-space observations
Minimum Kolmogorov Distance Estimates of Parameters an Parametrized Distributions.
Minimum Variance Unbiased Estimation for the Zero Class. Truncated Bivariate Poisson and Logarithmic Series Distributions.
Minimum Variance Unbiased Estimation in the Pareto Distribution.
Minimum Variance Unbiased Estimation of Left Truncated Multivariate Modified Power Series Distribution.
Minimum Variance Unbiased Estimation of Left Truncated Multivariate Power Series Distributions.
Minimum Variance Unbiased Estimation of Multivariate Modified Power Series Distribution.