عنوان مقاله [English]
نویسنده [English]چکیده [English]
In this paper influence diagnostics in the semi parametric linear measurement error is studied when the problem of multicollinearity is exist. First to combat multicollinearity, some ridge estimators are proposed based the penalized corrected likelihood approach, then using case deletion method the influence measures are defined to detect influential observations. In continue it is shown these measures are function of residuals and leverages. Furthrer more local influence approach is developed based the penalized likelihood function for assessing the influence of points. A simulation study is performed to illustrate the efficiency of proposed ridge estimators based on the asymptotically mean square error. Finally, the influence diagnostic approaches are applied to a real data.