Multivariate sequential point estimation

On Nonparametric Sequential Point Estimation

On Sequential Nonparametric Estimation of Multivariate Lqcation

For the multivariate one-sample location model (relating to a diagonally symmetric distribution). sequential non-parametric (point as well as interval) estimators based on appropriate rank statistics are considered and their asymptotic properties studied. In this context. asymptotic risk-efficiency of the proposed estimators and asymptotic normality of the associated stopping times are establis...

Sequential Kernel Estimation of a Multivariate Regression Function

This paper presents a sequential estimation procedure for an unknown multivariate regression function. Observed regressors and noises of the model are supposed to be dependent and form sequences of dependent vectors and numbers respectively. Two types of estimators are considered. Both estimators are constructed on the basis of Nadaraya–Watson kernel estimators. First, sequential estimators wit...

Step change point estimation in the multivariate-attribute process variability using artificial neural networks and maximum likelihood estimation

In some statistical process control applications, the combination of both variable and attribute quality characteristics which are correlated represents the quality of the product or the process. In such processes, identification the time of manifesting the out-of-control states can help the quality engineers to eliminate the assignable causes through proper corrective actions. In this paper, f...

Point and interval estimation following a sequential clinical trial

The usual methodology employed in analysis after a sequential clinical trial is based on orderings of the possible samples resulting from the design. However, this approach lacks flexibility for use in wider applications. In this paper two estimation techniques not based on orderings are considered and modified to obtain improved accuracy. A bias-adjusted maximum likelihood estimate together wi...