The main purpose of this paper is to give an algorithm to attain joint normality of non-normal multivariate observations through a new power normal family introduced by the author (Isogai, 1999). The algorithm tries to transform each marginal variable simultaneously to joint normality, but due...

We considered the problem of estimating effects in the following linear model for data arranged in a two-way table: Response = Common effect + Row effect + Column effect + Residual. This work was occasioned by a project to analyse Federal Aviation Administration (FAA) data on daily temporal...

Tsou (2003a) proposed a parametric procedure for making robust inference for mean regression parameters in the context of generalized linear models. This robust procedure is extended to model variance heterogeneity. The normal working model is adjusted to become asymptotically robust for...

Competition between neighbouring units in field experiments is a serious source of bias. The study of a competing situation needs construction of an environment in which it can happen and the competing units have to appear in a predetermined pattern. This paper describes methods of constructing...

The inclusion of linear deterministic effects in a time series model is important to get an appropriate specification. Such effects may be due to calendar variation, outlying observations or interventions. This article proposes a two-step method for estimating an adjusted time series and the...

We develop Bayesian procedures to make inference about parameters of a statistical design with autocorrelated error terms. Modelling treatment effects can be complex in the presence of other factors such as time; for example in longitudinal data. In this paper, Markov chain Monte Carlo methods...

Optimal statistical process control (SPC) requires models of both in-control and out-of-control process states. Whereas a normal distribution is the generally accepted model for the in-control state, there is a doubt as to the existence of reliable models for out-of-control cases. Various...

Two approaches have been used for designing spatial surveys to detect a target. The classical approach controls the probability of missing a target that exists; a Bayesian approach controls the probability that a target exists given that none was seen. In both cases, information about the likely...

In this article, we extended the widely used Bland-Altman graphical technique of comparing two measurements in clinical studies to include an analytical approach using a linear mixed model. The proposed statistical inferences can be conducted easily by commercially available statistical software...

A residual-based test for cointegration is proposed. The method of two-stage least squares is used to estimate the cointegration model parameters. The residuals are then tested for the existence of a unit root using the augmented Dickey-Fuller test.