Convienience wrapper for predict.GAMBoost, for obtaining predictions at specified boosting steps from a GAMBoost object fitted by GLMBoost.
● Data Source:
CranContrib
● Keywords: models
● Alias: predict.GLMBoost
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0 images
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Obtains predictions at specified boosting steps from a GAMBoost object fitted by GAMBoost.
● Data Source:
CranContrib
● Keywords: models
● Alias: predict.GAMBoost
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0 images
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plot.GAMBoost
(Package: GAMBoost) :
Plots of the smooth functions from a GAMBoost fit
Generates plots for the smooth components from a GAMBoost fit at a specific boosting step.
● Data Source:
CranContrib
● Keywords: models
● Alias: plot.GAMBoost
●
3 images
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optimStepSizeFactor
(Package: GAMBoost) :
Coarse line search for optimum step-size modification factor
This routine helps in finding an optimum step-size modification factor for GAMBoost, i.e., that results in an optimum in terms of cross-validated log-likelihood.
● Data Source:
CranContrib
● Keywords: models
● Alias: optimStepSizeFactor
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0 images
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optimGLMBoostPenalty
(Package: GAMBoost) :
Coarse line search for adequate GLMBoost penalty parameter
This routine is a convenience wrapper around optimGAMBoostPenalty for finding a penalty value that leads to an “optimal” number of boosting steps for GLMBoost (determined by AIC or cross-validation) that is not too small/in a specified range.
● Data Source:
CranContrib
● Keywords: models
● Alias: optimGLMBoostPenalty
●
0 images
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optimGAMBoostPenalty
(Package: GAMBoost) :
Coarse line search for adequate GAMBoost penalty parameter
This routine helps in finding a penalty value that leads to an “optimal” number of boosting steps for GAMBoost (determined by AIC or cross-validation) that is not too small/in a specified range.
● Data Source:
CranContrib
● Keywords: models
● Alias: optimGAMBoostPenalty
●
0 images
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getGAMBoostSelected
(Package: GAMBoost) :
Identify selected/significant covariates from a GAMBoost object
Extracts the information from a GAMBoost object which covariates have received any update up to a specific boosting step and for which smooth estimates the pointwise confidence bands do not contain the zero line.
● Data Source:
CranContrib
● Keywords: models
● Alias: getGAMBoostSelected
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0 images
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estimPVal
(Package: GAMBoost) :
Estimate p-values for a model fitted by GAMBoost or GLMBoost
Performs permutation-based p-value estimation for the optional covariates in a fit from GAMBoost or GAMBoost. Currently binary response models with linear effects are supported, and the components have to be selected with criterion="score"
● Data Source:
CranContrib
● Keywords: models
● Alias: estimPVal
●
0 images
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cv.GLMBoost
(Package: GAMBoost) :
Cross-validation for GLMBoost fits
Performs a convenience wrapper around cv.GAMBoost for performing a K-fold cross-validation for GLMBoost in search for the optimal number of boosting steps.
● Data Source:
CranContrib
● Keywords: models
● Alias: cv.GLMBoost
●
0 images
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cv.GAMBoost
(Package: GAMBoost) :
Cross-validation for GAMBoost fits
Performs a K-fold cross-validation for GAMBoost in search for the optimal number of boosting steps.
● Data Source:
CranContrib
● Keywords: models
● Alias: cv.GAMBoost
●
0 images
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