Add to ORKG• This paper develops statistical inference in linear models, dealing with the theory of maximum likelihood estimates and likelihood ratio tests under some linear inequality restrictions on the regression coefficients. The results are widely applicable to models used in environmental risk analysis and econometrics. Key-Words: • likelihood ratio test; linear constrains; regression models. AMS Subject Classification
The aim of this chapter is to review likelihood ratio test procedures in multivariate linear models,...
The goal of our article is to provide a transparent, robust, and computationally feasible statistica...
This paper develops three asymptotically equivalent tests for examining the validity of imposing lin...
This letter shows how to extend a number of published results on Bartlett and Bartlett-type correcti...
Maximum likelihood (ML) estimation for linear models with longitudinal data under inequality restric...
In this paper, we use a maximal invariant likelihood (MIL) to construct two likelihood ratio (LR) te...
We investigate the likelihood ratio test for a hypothesis regarding the dimension of the Σ-envelope ...
We consider the problem of testing for zero variance components in linear mixed models with correlat...
We investigate the likelihood ratio test for a hypothesis regarding the dimension of the Sigma-envel...
We propose likelihood and restricted likelihood ratio tests for goodness-of-fit of nonlinear regress...
Thesis (Ph.D.)--University of Washington, 2020This dissertation studies the problem of uniform infer...
In this paper, we use a maximal invariant likelihood (MIL) to construct two likelihood ratio (LR) te...
We consider inference in the linear regression model with one endogenous variable and potentially we...
A new method for testing linear restrictions in linear regression models is suggested
Key Words: hypothesis tests; longitudinal data; multivariate tests; order restrictions; re-peated me...
The aim of this chapter is to review likelihood ratio test procedures in multivariate linear models,...
The goal of our article is to provide a transparent, robust, and computationally feasible statistica...
This paper develops three asymptotically equivalent tests for examining the validity of imposing lin...
This letter shows how to extend a number of published results on Bartlett and Bartlett-type correcti...
Maximum likelihood (ML) estimation for linear models with longitudinal data under inequality restric...
In this paper, we use a maximal invariant likelihood (MIL) to construct two likelihood ratio (LR) te...
We investigate the likelihood ratio test for a hypothesis regarding the dimension of the Σ-envelope ...
We consider the problem of testing for zero variance components in linear mixed models with correlat...
We investigate the likelihood ratio test for a hypothesis regarding the dimension of the Sigma-envel...
We propose likelihood and restricted likelihood ratio tests for goodness-of-fit of nonlinear regress...
Thesis (Ph.D.)--University of Washington, 2020This dissertation studies the problem of uniform infer...
In this paper, we use a maximal invariant likelihood (MIL) to construct two likelihood ratio (LR) te...
We consider inference in the linear regression model with one endogenous variable and potentially we...
A new method for testing linear restrictions in linear regression models is suggested
Key Words: hypothesis tests; longitudinal data; multivariate tests; order restrictions; re-peated me...
The aim of this chapter is to review likelihood ratio test procedures in multivariate linear models,...
The goal of our article is to provide a transparent, robust, and computationally feasible statistica...
This paper develops three asymptotically equivalent tests for examining the validity of imposing lin...