an R package for multivariate smoothing using Iterative Bias Reduction smoother.
We are interested in smoothing (the values of) a vector of n observations y by d covariates measured at the same n observations (gathered in the matrix X). The iterated Bias Reduction produces a sequence of smoothers
\hat y=S_k y =(I - (I-S)^k)y,
where S is the pilot smoother which can be either a kernel or a thin plate spline smoother. In case of a kernel smoother, the kernel is built as a product of univariate kernels.
The most important parameter of the iterated bias reduction is
iterationsr. Usually this parameter is unknown and is
chosen from the search grid
K to minimize the criterion (GCV,
AIC, AICc, BIC or gMDL).
The user must choose the pilot smoother (kernel
"k", thin plate splines
"tps" or Duchon splines
plus the values of bandwidths (kernel)
or λ thin plate splines). As the choice of these raw
values depend on each particular dataset, one
can rely on effective degrees of freedom or default values given as degree of
freedom, see argument
df of the main function
Index of functions to be used by end user:
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ibr: Iterative bias reduction smoothing plot.ibr: Plot diagnostic for an ibr object predict.ibr: Predicted values using iterative bias reduction smoothers forward: Variable selection for ibr (forward method) print.summary.ibr: Printing iterative bias reduction summaries summary.ibr: Summarizing iterative bias reduction fits
Pierre-Andre Cornillon, Nicolas Hengartner, Eric Matzner-Lober
Maintainer: Pierre-Andre Cornillon <firstname.lastname@example.org>
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