FKSUM v0.1.0


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Fast Kernel Sums

Implements the method of Hofmeyr, D.P. (2019) <10.1109/TPAMI.2019.2930501> for fast evaluation of univariate kernel smoothers based on recursive computations. Applications to the basic problems of density and regression function estimation are provided, as well as some projection pursuit methods for which the objective is based on non-parametric functionals of the projected density, or conditional density of a response given projected covariates.

Functions in FKSUM

Name Description
cbin_alloc Allocation of points to bins
fk_ICA Independent component analysis with sample entropy estimated via kernel density
f_ppr Projection index for projection pursuit regression
df_ppr Gradient of the projection index for projection pursuit regression
dksum Kernel derivative sums
FKSUM-package Fast Exact Kernel Smoothing
f_ica Projection index for independent component analysis.
fancy_PPR_initialisation Initialisation for PPR based on Ridge LM after GAM type smoothing
df_ica Gradient of projection index for independent component analysis.
bin_wts Compute discrete bin weights
fk_md_dp C++ code for evaluating partial gradient of mimimum density hyperplane w.r.t. projected data
fk_md_b Minimum density hyperplane orthogonal to a vector
fk_md C++ code for evaluating mimimum density hyperplane from projected data
fk_mdh Minimum density hyperplanes
fk_fmdh Projection index for finding minimum density hyperplanes
fk_dfmdh Gradient of projection index for finding minimum density hyperplanes
fk_NW Nadaraya-Watson regression estimator
fk_density Fast univariate kernel density estimation
fk_loc_lin Local linear regression estimator
fk_is_minim_md Check if MDH constraints are active
kndksum Kernel and kernel derivative sums
fk_sum Fast Exact Kernel Sum Evaluation
norm_const_K Normalising constant for kernels in FKSUM
h_K_to_Gauss Bandwidth conversion to Gaussian
norm_K The L2 norm of a kernel
fk_ppr Projection pursuit regression with local linear kernel smoother
kLLreg Leave-one-out regression smoother
fk_regression Fast univariate kernel regression
h_Gauss_to_K Bandwidth conversion from Gaussian
whiten Whitening (standardising) a data matrix
var_K Variance of a kernel
ksum Kernel sums
roughness_K Kernel roughness
sm_bin_wts Compute smoothed bin weights
plot_kernel Plot the shape of a kernel function implemented in FKSUM based on its vector of beta coefficients
predict.fk_ppr Predict method for class fk_ppr
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Type Package
License GPL
Encoding UTF-8
LinkingTo Rcpp, RcppArmadillo
LazyData true
NeedsCompilation yes
Packaged 2019-11-29 14:59:43 UTC; david
Repository CRAN
Date/Publication 2019-12-02 16:40:06 UTC

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