On Diagnostics in Stochastic Restricted Linear Regression Models
نویسندگان
چکیده
منابع مشابه
On Diagnostics in Stochastic Restricted Linear Regression Models
The aim of this paper is to propose some diagnostic methods in stochastic restricted linear regression models. A review of stochastic restricted linear regression models is given. For the model, this paper studies the method and application of the diagnostic mostly. Firstly, review the estimators of this model. Secondly, show that the case deletion model is equivalent to the mean shift outlier ...
متن کاملRidge Stochastic Restricted Estimators in Semiparametric Linear Measurement Error Models
In this article we consider the stochastic restricted ridge estimation in semipara-metric linear models when the covariates are measured with additive errors. The development of penalized corrected likelihood method in such model is the basis for derivation of ridge estimates. The asymptotic normality of the resulting estimates are established. Also, necessary and sufficient condition...
متن کاملStochastic Restricted Two-Parameter Estimator in Linear Mixed Measurement Error Models
In this study, the stochastic restricted and unrestricted two-parameter estimators of fixed and random effects are investigated in the linear mixed measurement error models. For this purpose, the asymptotic properties and then the comparisons under the criterion of mean squared error matrix (MSEM) are derived. Furthermore, the proposed methods are used for estimating the biasing parameters. Fin...
متن کاملRestricted methods in symmetrical linear regression models
In this paper we discuss the problem of testing equality and inequality constraints in symmetrical linear regression models. This class of models includes all symmetric continuous distributions, such as normal, Student-t, Pearson VII, power exponential and logistic, among others. It is commonly used for the analysis of data containing influential or outlying observations with responses supposed...
متن کاملLiu Estimates and Influence Analysis in Regression Models with Stochastic Linear Restrictions and AR (1) Errors
In the linear regression models with AR (1) error structure when collinearity exists, stochastic linear restrictions or modifications of biased estimators (including Liu estimators) can be used to reduce the estimated variance of the regression coefficients estimates. In this paper, the combination of the biased Liu estimator and stochastic linear restrictions estimator is considered to overcom...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Open Journal of Statistics
سال: 2014
ISSN: 2161-718X,2161-7198
DOI: 10.4236/ojs.2014.49071