Reference

Local polinomial estimation

Nonparametric estimation of a mean function (the functional trend), a functional variance or a semivariogram.

npfda-package npfda

npfda: Nonparametric functional data analysis

npf.model() residuals(<npf.model>) plot(<npf.model>)

Nonparametric functional model

npf.fit()

Fit a nonparametric functional model

locpol(<npf.data>) locpol(<npf.bin>) predict(<npf.locpol>) residuals(<npf.locpol>) plot(<npf.locpol>)

Local polynomial trend estimation

np.var() predict(<npf.var>)

Local polynomial variance estimation

np.svar(<npf.data>) np.svar(<npf.locpol>)

Local polynomial estimation of the (intra-curve) semivariogram

Bandwidth selection

Cross-validation methods for bandwidth selection in local polynomial kernel smoothing.

h.cv(<npf.bin>) h.cv(<npf.bin.res2>)

Cross-validation methods for bandwidth selection

Binning

Methods for multidimensional binning.

npf.binning()

Binning of functional data

npf.bin.res2()

Binning of squared residuals of a local polynomial fit

svar.bin(<npf.data>) svar.bin(<npf.locpol>)

Empirical (intra-curve) variogram estimate

Functional data

S3 class npf.data and methods.

npf.data() coords(<npf.data>)

Functional data (S3 class "npf.data")

f.mean() f.var()

Sample functional mean and variance

plot(<npf.data>)

Plot functional data

Data sets

Data sets included in the package.

ozone

Ground-level ozone

Other packages

Utilities to interact with other packages.

as.fds()

Converts functional data to a fds object

Utilities

Other utilities…

locpol(<npf.data>) locpol(<npf.bin>) predict(<npf.locpol>) residuals(<npf.locpol>) plot(<npf.locpol>)

Local polynomial trend estimation

np.var() predict(<npf.var>)

Local polynomial variance estimation

npf.model() residuals(<npf.model>) plot(<npf.model>)

Nonparametric functional model