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R: Sample size estimation for BE decision via FDA method for...
sampleN.HVNTID {PowerTOST} R Documentation Sample size estimation for BE decision via FDA method for highly variable (HV) narrow therapeutic index drugs (NTIDs)...
/CRAN/refmans/PowerTOST/html/sampleN.HVNTID.html
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R: The generalized correlated cross-validation (GCCV) score
...S {fda.usc} R Documentation The generalized correlated cross-validation (GCCV) score Description Compute the generalized correlated cross-validation (GCV) score. Usage GCV.S( y, S, criteria = "GCV", W...
/CRAN/refmans/fda.usc/html/GCV.S.html
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R: Computes Cross-validated Error Sum of Integrated Squared...
fRegress.CV {fda} R Documentation Computes Cross-validated Error Sum of Integrated Squared Errors for a Functional Regression Model Description For a functional regression model, a cross-validated...
/CRAN/refmans/fda/html/fRegress.CV.html
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R: Cross-validation Functional Regression with scalar response...
fregre.basis.cv {fda.usc} R Documentation Cross-validation Functional Regression with scalar response using basis representation. Description Computes functional regression between functional...
/CRAN/refmans/fda.usc/html/fregre.basis.cv.html
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R: Cross-validation functional regression with scalar response...
fregre.np.cv {fda.usc} R Documentation Cross-validation functional regression with scalar response using kernel estimation. Description Computes functional regression between functional explanatory...
/CRAN/refmans/fda.usc/html/fregre.np.cv.html
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R: The cross-validation (CV) score
CV.S {fda.usc} R Documentation The cross-validation (CV) score Description Compute the leave-one-out cross-validation score. Usage CV.S(y, S, W = NULL, trim = 0, draw = FALSE, metric = metric.lp...
/CRAN/refmans/fda.usc/html/CV.S.html
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R: Cross-validation for the S-LASSO estimator
...-validation for the S-LASSO estimator Description K-fold cross-validation procedure to choose the tuning parameters for the S-LASSO estimator (Centofanti et al., 2020). Usage slasso.fr_cv( Y_fd, X_fd...
/CRAN/refmans/slasso/html/slasso.fr_cv.html
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R: Cross validation for the regularised and flexible...
...validation for the regularised and flexible discriminant analysis with compositional data using the \alpha-transformation Description Cross validation for the regularised and flexible discriminant...
/CRAN/refmans/Compositional/html/alfarda.tune.html
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R: The generalized correlated cross-validation (GCCV) score.
GCCV.S {fda.usc} R Documentation The generalized correlated cross-validation (GCCV) score. Description The generalized correlated cross-validation (GCV) score. Usage GCCV.S( y, S, criteria = "GCCV1", W...
/CRAN/refmans/fda.usc/html/GCCV.S.html
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R: Cross validation for the alpha-k-NN regression with...
...validation for the \alpha-k-NN regression with compositional predictor variables Description Cross validation for the \alpha-k-NN regression with compositional predictor variables. Usage alfaknnreg...
/CRAN/refmans/Compositional/html/alfaknnreg.tune.html
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R: Cross validation for the alpha-kernel regression with...
...Cross validation for the \alpha-kernel regression with compositional response data Description Cross validation for the \alpha-kernel regression with compositional response data. Usage akernreg.tune(y...
/CRAN/refmans/Compositional/html/akernreg.tune.html
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R: Cross validation for the alpha-k-NN regression with...
...Cross validation for the \alpha-k-NN regression with compositional response data Description Cross validation for the \alpha-k-NN regression with compositional response data. Usage aknnreg.tune(y, x...
/CRAN/refmans/Compositional/html/aknnreg.tune.html
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R: Cross-Validation and Bootstrapping over Curves
validateFDboost {FDboost} R Documentation Cross-Validation and Bootstrapping over Curves Description DEPRECATED! The function validateFDboost() is deprecated, use applyFolds and bootstrapCI instead.
/CRAN/refmans/FDboost/html/validateFDboost.html
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R: Cross-Validation and Bootstrapping over Curves
...Cross-Validation and Bootstrapping over Curves Description Cross-validation and bootstrapping over curves to compute the empirical risk for hyper-parameter selection. Usage applyFolds( object, folds...
/CRAN/refmans/FDboost/html/applyFolds.html
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R: Functional Neural Networks with Cross-validation
fnn.cv {FuncNN} R Documentation Functional Neural Networks with Cross-validation Description This is a convenience function for the user. The inputs are largely the same as the fnn.fit() function...
/CRAN/refmans/FuncNN/html/fnn.cv.html
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R: Functional Data Analysis and Utilities for Statistical Computing
...Q R S T U V W X misc fda.usc-package Functional Data Analysis and Utilities for Statistical Computing (fda.usc) -- A -- accuracy Performance measures for regression and classification models Adot PCvM...
/CRAN/refmans/fda.usc/html/00Index.html
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R: Functional penalized PLS regression with scalar response...
...penalized principal componentes PPLS through cross-validation. The algorithm selects the PPLS components with best estimates the response. The selection is performed by cross-validation (CV) or Model...
/CRAN/refmans/fda.usc/html/fregre.pls.cv.html
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R: Functional penalized PC regression with scalar response using...
...using selection of number of (penalized) principal components PC through cross-validation. The algorithm selects the PC with best estimates the response. The selection is performed by cross-validation...
/CRAN/refmans/fda.usc/html/fregre.pc.cv.html
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R: Compute GCV Criterion
lambda2gcv {fda} R Documentation Compute GCV Criterion Description The generalized cross-validation or GCV criterion is often used to select an appropriate smoothing parameter value, by finding...
/CRAN/refmans/fda/html/lambda2gcv.html
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R: Kernel functional partial least squares method
...kernel is used. Usage KFPLS(X, Y, obser_time, nfold, n_comp, sigm_list, basis) Arguments X An array with three indices. The (i, j, k)-th element of it corresponds to the measurment of the i-th subject...
/CRAN/refmans/KFPLS/html/KFPLS.html
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