We describe some recent developments in PcGets, and consider their impact on its performance across different (unknown) states of nature. We discuss the consistency of its selection procedures, and examine the extent to which model selection is non-distortionary at relevant sample sizes. The problems posed in judging performance on collinear data are noted. We also describe how PcGets has been extended to assist non-experts in model formulation, handle more variables than observa-tions and tackle non-linear models
This review examines the facilities provided by PcGets version 1.0, an OxMetrics module designed to ...
This review examines the facilities provided by PcGets version 1.0, an OxMetrics module designed to ...
When the DGP is nested in the model, PcGets delivers high performance selection across different (un...
We describe some recent developments in PcGets, and consider their impact on its performance across ...
After reviewing the simulation performance of general-to-specific automatic regression-model selecti...
We describe some recent developments in PcGets, and consider their impact on its performance across ...
After reviewing the simulation performance of general-to-specific automatic regression-model selecti...
We consider the analytic basis for PcGets, an Ox Package implementing automatic generalto- specific ...
We consider the analytic basis for PcGets, an Ox Package implementing automatic general-to-specific ...
We establish the consistency of the selection procedures embodied in PcGets, and compare their perfo...
Model selection is ubiquitous as we simply do not know the underlying data generating process. Howev...
The paper describes two automatic model selection algorithms, RETINA and PcGets, briefly discussing ...
The properties of automatic model selection are discussed, focusing on PcGets. We explain the backgr...
Disputes about econometric methodology partly reflect a lack of evidence on alternative approaches. ...
Disputes about econometric methodology partly reflect a lack of evidence on alternative approaches. ...
This review examines the facilities provided by PcGets version 1.0, an OxMetrics module designed to ...
This review examines the facilities provided by PcGets version 1.0, an OxMetrics module designed to ...
When the DGP is nested in the model, PcGets delivers high performance selection across different (un...
We describe some recent developments in PcGets, and consider their impact on its performance across ...
After reviewing the simulation performance of general-to-specific automatic regression-model selecti...
We describe some recent developments in PcGets, and consider their impact on its performance across ...
After reviewing the simulation performance of general-to-specific automatic regression-model selecti...
We consider the analytic basis for PcGets, an Ox Package implementing automatic generalto- specific ...
We consider the analytic basis for PcGets, an Ox Package implementing automatic general-to-specific ...
We establish the consistency of the selection procedures embodied in PcGets, and compare their perfo...
Model selection is ubiquitous as we simply do not know the underlying data generating process. Howev...
The paper describes two automatic model selection algorithms, RETINA and PcGets, briefly discussing ...
The properties of automatic model selection are discussed, focusing on PcGets. We explain the backgr...
Disputes about econometric methodology partly reflect a lack of evidence on alternative approaches. ...
Disputes about econometric methodology partly reflect a lack of evidence on alternative approaches. ...
This review examines the facilities provided by PcGets version 1.0, an OxMetrics module designed to ...
This review examines the facilities provided by PcGets version 1.0, an OxMetrics module designed to ...
When the DGP is nested in the model, PcGets delivers high performance selection across different (un...