The choice of the appropriate linear model before this can be used for planning and decision making, has been the concern of many statistical workers. Most of the methods in the literature aim at evaluating the descriptive ability of the candidate models. In the present paper an evaluation...

In this paper, an evaluation method is suggested for selecting one of two competing models based on certain predictive ability ratings. The main focus is on the case of linear models that are not necessarily nested. In the context of such models, the test procedure is based on a sample statistic...

The paper deals with a distribution that arises as the distribution of a sample statistic used to compare the predictive ability of two competing linear models. It is defined as the distribution of the ratio of two correlated gamma variables and its probabilities are tabulated in order that they...

The paper considers the problem of selecting one of two not necessarily nested competing regression models based on comparative evaluations of their abilities in each of two different issues: The first pertains to viewing the problem as a “best-fitting” model determination problem in the...

Woodall and Montgomery in a discussion paper, state that multivariate process control is one of the most rapidly developing sections of statistical process control. Nowadays, in industry, there are many situations in which the simultaneous monitoring or control, of two or more related quality -...

In this paper we discuss the basic procedures for the implementation of multivariate statistical process control via control charting. Furthermore, we review multivariate extensions for all kinds of univariate control charts, such as multivariate Shewhart-type control charts, multivariate CUSUM...