MSE.BSGS
(Package: BSGS) :
Mean square error (MSE).
Calculate the mean square error for the sparse group selection problems.
● Data Source:
CranContrib
● Keywords:
● Alias: MSE.BSGS
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BSGS.Simple
(Package: BSGS) :
The group-wise Gibbs sampler for sparse group selection.
Generate the posterior samples to perform Bayesian sparse group selection to identify the important groups of variables and variables within those.
● Data Source:
CranContrib
● Keywords:
● Alias: BSGS.Simple
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CompWiseGibbsSimple
(Package: BSGS) :
Generate the posterior samples from the posterior distribution using the component-wise Gibbs sampler (CWGS).
Generate the posterior samples using MCMC procedures.
● Data Source:
CranContrib
● Keywords:
● Alias: CompWiseGibbsSimple
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Crisis2008
(Package: BSGS) :
A cross-sectional data set from Rose and Spiegel.
A cross-sectional data set from Rose and Spiegel (2011), which is available at http://faculty.haas.berkeley.edu/arose. The response varialbe is 2008-2009 growth rate for the cirsis measure. This dataset consisits of 119 explanatory factors for the crisis for as many as 107 countries, but there are data missing for a number of countries.
● Data Source:
CranContrib
● Keywords:
● Alias: Crisis2008
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BSGS.Sample
(Package: BSGS) :
Sample version of group-wise Gibbs sampler for sparse group selection.
Generate the posterior samples by an approximation sampling method to perform Bayesian sparse group selection to identify the important groups of variables and variables within those.
● Data Source:
CranContrib
● Keywords:
● Alias: BSGS.Sample
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CompWiseGibbsSMP
(Package: BSGS) :
Stochastic matching pursuit for variable selection.
Perform MCMC procedure to generate the posterior samples to estimate posterior quantities of interest in Bayesian variable selection using stochastic matching pursuit approach (SMP).
● Data Source:
CranContrib
● Keywords:
● Alias: CompWiseGibbsSMP
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CGS.SMP.PE
(Package: BSGS) :
Posterior estimates of parameters.
Calculate the posterior estimates of parameters based on the samples generated from the posterior distribution by the stochastic matching pursuit (SMP).
● Data Source:
CranContrib
● Keywords:
● Alias: CGS.SMP.PE
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BSGS.PE
(Package: BSGS) :
Posterior estimates of parameters.
Provide the posterior estimates of parameters.
● Data Source:
CranContrib
● Keywords:
● Alias: BSGS.PE
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TCR.TPR.FPR.CGS.SMP
(Package: BSGS) :
Evaluate TCR, TPR and FPR for variable selection problems.
Calculate the true classification rate (TCR), the true positive rate (TPR), and the false positive rate (FPR).
● Data Source:
CranContrib
● Keywords:
● Alias: TCR.TPR.FPR.CGS.SMP
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Crisis2008BalancedData
(Package: BSGS) :
A cross-sectional data set from Rose and Spiegel with the removal of missing values.
A cross-sectional data set from Rose and Spiegel (2011), which is available at http://faculty.haas.berkeley.edu/arose. The response varialbe is 2008-2009 growth rate for the cirsis measure. Rose and Spiegel originally consider 119 explanatory factors for the crisis for as many as 107 countries, but there are data missing for a number of countries. To maintain a balanced data set, we use 51 regressors for a sample of 72 countries. These regressors can be classified into the nine theoretical groups of the crisis' origin (the number in parentheses indicates the number of variables considered in the group): principal factors (10), financial policies (three), financial conditions (four), asset price appreciation (two), macroeconomic policies (four), institutions (11), geography (four), financial linkages (one), and trade linkages (12).
● Data Source:
CranContrib
● Keywords:
● Alias: Crisis2008BalancedData
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