the aim of this paper is to propose some diagnostic methods in linear ridge measurement error models with stochastic linear restrictions using the corrected likelihood. based on the bias-corrected estimation of model parameters, diagnostic measures are developed to identify outlying and influential observations. in addition, we derive the corrected score test statistic for outliers detection ba...

Outliers and influential observations have important effects on the regression analysis. The goal of this paper is to extend the mean-shift model for detecting outliers in case of ridge regression model in the presence of stochastic linear restrictions when the error terms follow by an autoregressive AR(1) process. Furthermore, extensions of measures for diagnosing influential observations are ...

In this paper, we present case deletion and mean shift outlier models for linear mixed measurement error models using the corrected likelihood of Nakamura (1990). We derive the corrected score test statistic for outliers detection based on mean shift outlier models. Furthermore, several case deletion diagnostics are constructed as a tool for influence diagnostics. It is found that they can be w...

Outlier detection has been a long-debated subject among researchers due to its effect on model fitting. Spatial outlier received considerable attention in the recent past. On other hand, accommodation, particularly spatial applications, retains vital information about model. It is pertinent develop method that capable of accommodating detected outliers fashion models. In this paper, we formulat...

Outlier detection statistics based on two models, the case-deletion model and the mean-shift model, are developed in the context of a multivariate linear regression model. These are generalizations of the univariate Cook’s distance and other diagnostic statistics. Approximate distributions of the proposed statistics are also obtained to get suitable cutoff points for significance tests. In addi...

The aim of this paper is to propose some diagnostic methods in linear ridge measurement error models with stochastic linear restrictions using the corrected likelihood. Based on the bias-corrected estimation of model parameters, diagnostic measures are developed to identify outlying and influential observations. In addition, we derive the corrected score test statistic for outliers detection ba...