Add to ORKGThe asymptotic properties of parameter estimators which are based on a model that has been selected by a model selection procedure are investigated. In particular, the asymptotic distribution is derived and the effects of the model selection process on subsequent inference are illustrated.
textabstractModel selection can involve several variables and selection criteria. A simple method to...
Eigenschaften von Inferenzprozeduren der traditionellen Inferenzstatistik wurden in den letzten Jahr...
Inference after model selection is a very important problem. This paper derives the asymptotic distr...
Plug-in estimation and corresponding refinements involving penalisation have been considered in vari...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
Ignoring the model selection step in inference after selection is harmful. This paper studies the as...
Ignoring the model selection step in inference after selection is harmful. This paper studies the as...
In reading the two articles written by Hjort and Claeskens, readers will � nd several important and ...
We argue that model selection uncertainty should be fully incorporated into statistical inference wh...
In certain cases statistical methods based on standard maximum likelihood asymptotics become valid a...
The problem of statistical model selection in econometrics and statistics is reviewed. Model selecti...
This paper evaluates the properties of a joint and sequential estimation procedure for estimating th...
Although model selection is routinely used in practice nowadays, little is known about its precise e...
Variable selection methods and model selection approaches are valuable statistical tools, which are ...
AbstractSuppose that independent observations come from an unspecified unknown distribution. Then we...
textabstractModel selection can involve several variables and selection criteria. A simple method to...
Eigenschaften von Inferenzprozeduren der traditionellen Inferenzstatistik wurden in den letzten Jahr...
Inference after model selection is a very important problem. This paper derives the asymptotic distr...
Plug-in estimation and corresponding refinements involving penalisation have been considered in vari...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
Ignoring the model selection step in inference after selection is harmful. This paper studies the as...
Ignoring the model selection step in inference after selection is harmful. This paper studies the as...
In reading the two articles written by Hjort and Claeskens, readers will � nd several important and ...
We argue that model selection uncertainty should be fully incorporated into statistical inference wh...
In certain cases statistical methods based on standard maximum likelihood asymptotics become valid a...
The problem of statistical model selection in econometrics and statistics is reviewed. Model selecti...
This paper evaluates the properties of a joint and sequential estimation procedure for estimating th...
Although model selection is routinely used in practice nowadays, little is known about its precise e...
Variable selection methods and model selection approaches are valuable statistical tools, which are ...
AbstractSuppose that independent observations come from an unspecified unknown distribution. Then we...
textabstractModel selection can involve several variables and selection criteria. A simple method to...
Eigenschaften von Inferenzprozeduren der traditionellen Inferenzstatistik wurden in den letzten Jahr...
Inference after model selection is a very important problem. This paper derives the asymptotic distr...