Add to ORKGPractical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to use computational tools. The aim of this contribution is to show that the implementation is not as hard as it might look at the first sight. We will illustrate this point by showing how higher-order asymptotics for heteroscedastic regression models may be easily implemented into S-PLU
The likelihood function represents the basic ingredient of many commonly used statistical methods fo...
This paper focuses on the application of higher-order asymptotics for likelihood-based inference to ...
This paper deals with the application of higher order asymptotics for likelihood-based inference to ...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
One of the main criticisms against the use of higher order asymptotics is that the algebraic express...
One of the main criticisms against the use of higher order asymptotics is that the algebraic express...
One of the main criticisms against the use of higher order asymptotics is that the algebraic express...
The S-PLUS library HOA implements several of the most promising higher-order solutions for three wid...
The S-PLUS library HOA implements several of the most promising higher-order solutions for three wid...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
We discuss the effects of model misspecifications on higher-order asymptotic approximations of the ...
Likelihood-based approaches, including profile-likelihood, signed- likelihood, sample deviance and p...
This paper deals with the application of higher order asymptotics for likelihood-based inference to ...
The likelihood function represents the basic ingredient of many commonly used statistical methods fo...
This paper focuses on the application of higher-order asymptotics for likelihood-based inference to ...
This paper deals with the application of higher order asymptotics for likelihood-based inference to ...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
One of the main criticisms against the use of higher order asymptotics is that the algebraic express...
One of the main criticisms against the use of higher order asymptotics is that the algebraic express...
One of the main criticisms against the use of higher order asymptotics is that the algebraic express...
The S-PLUS library HOA implements several of the most promising higher-order solutions for three wid...
The S-PLUS library HOA implements several of the most promising higher-order solutions for three wid...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
Practical use of modern likelihood asymptotics is still limited by the lack of flexible and easy to ...
We discuss the effects of model misspecifications on higher-order asymptotic approximations of the ...
Likelihood-based approaches, including profile-likelihood, signed- likelihood, sample deviance and p...
This paper deals with the application of higher order asymptotics for likelihood-based inference to ...
The likelihood function represents the basic ingredient of many commonly used statistical methods fo...
This paper focuses on the application of higher-order asymptotics for likelihood-based inference to ...
This paper deals with the application of higher order asymptotics for likelihood-based inference to ...