Entropy Type Estimator to Simple Linear Measurement Error Models
نویسندگان
چکیده
منابع مشابه
Entropy Type Estimator to Simple Linear Measurement Error Models
Abstract: The classical maximum likelihood estimation fails to estimate the simple linear measurement error model, with or without equation error, unless additional assumptions are made about the structural parameters. In the literature there are six different assumptions that could be added in order to solve the measurement error models. In this paper, we proposed an entropy-type estimator bas...
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 کاملA New Ridge Estimator in Linear Measurement Error Model with Stochastic Linear Restrictions
In this paper, we propose a new ridge-type estimator called the new mixed ridge estimator (NMRE) by unifying the sample and prior information in linear measurement error model with additional stochastic linear restrictions. The new estimator is a generalization of the mixed estimator (ME) and ridge estimator (RE). The performances of this new estimator and mixed ridge estimator (MRE) against th...
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 کاملInfluence Measures in Ridge Linear Measurement Error Models
Usually the existence of influential observations is complicated by the presence of collinearity in linear measurement error models. However no method of influence measure available for the possible effect's that collinearity can have on the influence of an observation in such models. In this paper, a new type of ridge estimator based corrected likelihood function (REC) for linear measurement e...
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: Austrian Journal of Statistics
سال: 2016
ISSN: 1026-597X
DOI: 10.17713/ajs.v34i3.418