Add to ORKGSummary For the problem of model selection full crossvalidation has been proposed as alternative criterion to the traditional crossvalidation particularly in cases where the latter one is not well dened To justify the use of the new proposal we show that under some conditions both criteria share the same asymptotic optimality property when selecting among linear regression models AMS subject classications Primary J secondary J Key words Crossvalidation full crossvalidation model selection prediction asymptotic optimality One of the most popular methods for the selection of regression models is based on minimizing the crossvalidation CV criterion of Stone among an appropriate class of model candidates This may be particularl...
Several model selection criteria which generally can be classied as the penalized robust method are ...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
This article specializes the critical value (CV) methods that are based upon (refinements of) Bonfer...
For the problem of model selection, full cross-validation has been proposed as an alternative criter...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
We consider the problem of model (or variable) selection in the classical regression model based on ...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
In this paper we propose a cross-validation selection criterion to determine asymptotically the corr...
This article gives a robust technique for model selection in regression models, an important aspect ...
Model selection in nonparametric and semiparametric regression is of both theoretical and practical ...
The problem considered here is that of using a data-driven procedure to select a good estimate from ...
grantor: University of TorontoThe problem of determining which variables to keep in a lin...
grantor: University of TorontoThe problem of determining which variables to keep in a lin...
Several model selection criteria which generally can be classied as the penalized robust method are ...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
This article specializes the critical value (CV) methods that are based upon (refinements of) Bonfer...
For the problem of model selection, full cross-validation has been proposed as an alternative criter...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
We consider the problem of model (or variable) selection in the classical regression model based on ...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
In this paper we propose a cross-validation selection criterion to determine asymptotically the corr...
This article gives a robust technique for model selection in regression models, an important aspect ...
Model selection in nonparametric and semiparametric regression is of both theoretical and practical ...
The problem considered here is that of using a data-driven procedure to select a good estimate from ...
grantor: University of TorontoThe problem of determining which variables to keep in a lin...
grantor: University of TorontoThe problem of determining which variables to keep in a lin...
Several model selection criteria which generally can be classied as the penalized robust method are ...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
This article specializes the critical value (CV) methods that are based upon (refinements of) Bonfer...