Regression model, uncertain non-sample prior information, maximum likelihood, restricted, preliminary test and shrinkage estimators, bias, mean square error and relative efficiency, Primary 62F30, Secondary 62H12 and 62F10,
<p>Estimate intercept (.58) is the detection rate for 0 confidence, 0 agreement level, females and o...
In simple regression analyses, the inference on the intercept depends on the knowledge of the slope....
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
[Abstract]: This paper considers alternative estimators of the intercept parameter of the linear reg...
summary The estimation of the slope parameter of the linear regression model with normal error is co...
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression mo...
This paper considers estimation of the slope parameter of the linear regression model with Student-t...
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression mo...
This paper introduces and investigates a new pre-test estimator for the parameter vector of the line...
The estimation of the slope parameter of two linear regression models with normal errors are conside...
Classical inferences about population parameters are usually drawn from the sample data alone. This ...
Inference about population parameters could be improved using non-sample prior information (NSPI) fr...
Arguably the most widely used statistical technique is the linear model. Traditionally all classical...
AbstractFor a simple multivariate regression model, nonparametric estimation of the (vector of) inte...
The problem of parallelism for bi-linear regression lines arises in many real life investi-gations. ...
<p>Estimate intercept (.58) is the detection rate for 0 confidence, 0 agreement level, females and o...
In simple regression analyses, the inference on the intercept depends on the knowledge of the slope....
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
[Abstract]: This paper considers alternative estimators of the intercept parameter of the linear reg...
summary The estimation of the slope parameter of the linear regression model with normal error is co...
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression mo...
This paper considers estimation of the slope parameter of the linear regression model with Student-t...
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression mo...
This paper introduces and investigates a new pre-test estimator for the parameter vector of the line...
The estimation of the slope parameter of two linear regression models with normal errors are conside...
Classical inferences about population parameters are usually drawn from the sample data alone. This ...
Inference about population parameters could be improved using non-sample prior information (NSPI) fr...
Arguably the most widely used statistical technique is the linear model. Traditionally all classical...
AbstractFor a simple multivariate regression model, nonparametric estimation of the (vector of) inte...
The problem of parallelism for bi-linear regression lines arises in many real life investi-gations. ...
<p>Estimate intercept (.58) is the detection rate for 0 confidence, 0 agreement level, females and o...
In simple regression analyses, the inference on the intercept depends on the knowledge of the slope....
We consider two types of problems in maximum likelihood estimation of parameters of linear functions...
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