Asymptotical confidence region in a replicated mixed linear model with an estimated covariance matrix
Asymptotically Efficient Recursive Estimation for Incomplete Data Models Using the Observed Information.
Asymptotically minimax estimation of a constrained Poisson vector via polydisc transforms
Asymptotically minimax estimation of order-constrained parameters and eigenfunctions of the laplacian on the ball
Asymptotically Most Powerful Unbiased Tests in the Independent not Identically Distributed Case
Asymptotically normal confidence intervals for a determinant in a generalized multivariate Gauss-Markoff model
By using three theorems (Oktaba and Kieloch [3]) and Theorem 2.2 (Srivastava and Khatri [4]) three results are given in formulas (2.1), (2.8) and (2.11). They present asymptotically normal confidence intervals for the determinant in the MGM model , , scalar , with a matrix . A known random matrix has the expected value , where the matrix is a known matrix of an experimental design, is an unknown matrix of parameters and is the covariance matrix of being the symbol of the Kronecker...
Asymptotically normal estimation in the linear-fractional regression problem with random errors in coefficients.
Asymptotically normal estimation of a multidimensional parameter in the linear-fractional regression problem.
Asymptotically normal estimation of a parameter in a linear-fractional regression problem.
Asymptotically normal explicit estimation of parameters in the Michaelis--Menten equation.
Asymptotically optimal estimation in a linear fractional regression problem with random errors in coefficients.
Asymptotically optimal estimation in linear regression in the case of violation of some classical assumptions.
Asymptotically Optimal tests in the Independent not Identically Distributed case
Asymptotics for robust MOSUM
Asymptotische Verteilungen einiger Schätzverfahren bei Trend und Fehlern in den Variablen.
Bad luck in quadratic improvement of the linear estimator in a special linear model
The paper concludes our investigations in looking for the locally best linear-quadratic estimators of mean value parameters and of the covariance matrix elements in a special structure of the linear model (2 variables case) where the dispersions of the observed quantities depend on the mean value parameters. Unfortunately there exists no linear-quadratic improvement of the linear estimator of mean value parameters in this model.
Bayes and empirical bayes tests for the life parameter
We study the one-sided testing problem for the exponential distribution via the empirical Bayes (EB) approach. Under a weighted linear loss function, a Bayes test is established. Using the past samples, we construct an EB test and exhibit its optimal rate of convergence. When the past samples are not directly observable, we work out an EB test by using the deconvolution kernel method and obtain its asymptotic optimality.
BAYES Estimation for the Variance of a Finite Population.
Bayes estimation of the reliability function and hazard rate of a Weibull failure time distribution.
Given the recorded life times from a Weibull distribution, Bayes estimates of the reliability function and hazard rate are obtained using the posterior distributions and some recent results on Bayesian approximations due to Lindley (1980). Based on a Monte Carlo study, these estimates are compared with their maximum likelihood counterparts.
Bayes optimal stopping of a homogeneous poisson process under linex loss function and variation in the prior
A homogeneous Poisson process (N(t),t ≥ 0) with the intensity function m(t)=θ is observed on the interval [0,T]. The problem consists in estimating θ with balancing the LINEX loss due to an error of estimation and the cost of sampling which depends linearly on T. The optimal T is given when the prior distribution of θ is not uniquely specified.