Testing the Mean of a Normal Population Under Dependence

Robust tests for testing the parameters of a normal population

This article aims to provide a simple robust method to test the parameters of a normal population by using the new diagnostic tool called the “Forward Search” (FS) method. The most commonly used procedures to test the mean and variance of a normal distribution are Student’s t test and Chi-square test, respectively. These tests suffer from the presence of outliers. We introduce the FS version of...

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

robust tests for testing the parameters of a normal population

this article aims to provide a simple robust method to test the parameters of a normal population by using the new diagnostic tool called the “forward search” (fs) method. the most commonly used procedures to test the mean and variance of a normal distribution are student’s t test and chi-square test, respectively. these tests suffer from the presence of outliers. we introduce the fs version of...

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...