Perform an estimation of $H_0$

This function performs an estimation of $H_0$ used for the estimation of the bandwidth for a univariate kernel regression estimator defined over continuous domains data using the method of Golovkine et al. (2020).

estimate_H0(data, t0 = 0, k0 = 2, sigma = NULL)

Arguments

data	A list, where each element represents a curve. Each curve have to be defined as a list with two entries: $t The sampling points $x The observed points.
t0	Numeric, the sampling point at which we estimate $H0$ . We will consider the $8k0 - 7$ nearest points of $t_0$ for the estimation of $H_0$ when $\sigma$ is unknown.
k0	Numeric, the number of neighbors of $t_0$ to consider. Should be set as $k0 = M * exp(-log(log(M))^2)$ .
sigma	Numeric, true value of sigma. Can be NULL if true value is unknown.

Value

Numeric, an estimation of H0.

References

Golovkine S., Klutchnikoff N., Patilea V. (2020) - Learning the smoothness of noisy curves with applications to online curves denoising.

Perform an estimation of H0H_0

Arguments

Value

References

See also