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)
| data | A list, where each element represents a curve. Each curve have to be defined as a list with two entries:
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|---|---|
| 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. |
Numeric, an estimation of H0.
Golovkine S., Klutchnikoff N., Patilea V. (2020) - Learning the smoothness of noisy curves with applications to online curves denoising.
Other estimate \(H_0\):
estimate_H0_deriv_list(),
estimate_H0_deriv(),
estimate_H0_list()