estimate_bandwidth_mean: Perform an estimation of the bandwidth for the estimation of...

In StevenGolovkine/funestim: Nonparametric Kernel Smoothing Methods for Functional Data

Perform an estimation of the bandwidth for the estimation of the mean.

Description

This function performs an estimation of the bandwidth for a univariate kernel regression estimator defined over continuous data.

Usage

estimate_bandwidth_mean(
  curves,
  params,
  sigma = 0,
  grid_bandwidth = lseq(0.001, 0.1, length.out = 101),
  n_obs_min = 2,
  kernel_name = "epanechnikov"
)

Arguments

curves	List, where each element represents a curve. Each curve have to be defined as a list with two entries: $t Sampling points $x Observed points.
params	List, estimation of the different parameters: $point Time point where the smoothing has been done. $H Estimated regularity. $L Estimated constant. $var Estimated variance.
sigma	Numeric, estimation of the std of the noise σ.
grid_bandwidth	Vector (default = lseq(0.001, 0.1, length.out = 101)), grid of bandwidths.
n_obs_min	Integer (default = 2), minimum number of points in the neighborhood to keep the curve in the estimation.
kernel_name	String (default = 'epanechnikov'), the kernel used for the estimation: epanechnikov uniform biweight

Value

List, estimation of the bandwidth.

References

Golovkine S., Klutchnikoff N., Patilea V. (2021) - Adaptive estimation of irregular mean and covariance functions.

See Also

Other estimate bandwidth: estimate_bandwidth_covariance()

StevenGolovkine/funestim documentation built on June 15, 2022, 3:42 a.m.