Wavelet Shrinkage Generalized Bayes Estimation for Multivariate Normal Distribution Mean Vectors with unknown Covariance Matrix under Balanced-LINEX Loss

BAYES ESTIMATION USING A LINEX LOSS FUNCTION

This paper considers estimation of normal mean ? when the variance is unknown, using the LINEX loss function. The unique Bayes estimate of ? is obtained when the precision parameter has an Inverse Gaussian prior density

Estimating a Bounded Normal Mean Under the LINEX Loss Function

Let X be a random variable from a normal distribution with unknown mean θ and known variance σ2. In many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. As the usual estimator of θ, i.e., X under the LINEX loss function is inadmissible, finding some competitors for X becomes worthwhile. The only study in the literature considered the problem of min...

Estimation of the Multivariate Normal Mean under the Extended Reflected Normal Loss Function

Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices

In this paper, a shrinkage estimator for the population mean is proposed under known quadratic loss functions with unknown covariance matrices. The new estimator is nonparametric in the sense that it does not assume a specific parametric distribution for the data and it does not require the prior information on the population covariancematrix. Analytical results on the improvement of the propos...

Estimating a Bounded Normal Mean Under the LINEX Loss Function

Let X be a random variable from a normal distribution with unknown mean θ and known variance σ2. In many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. As the usual estimator of θ, i.e., X under the LINEX loss function is inadmissible, finding some competitors for X becomes worthwhile. The only study in the literature considered the problem of min...