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See references for details.

Usage

MVKE(d, v, h = 0.2, kernel = c("exp", "Gaussian"))

Arguments

d

The dataset. Should be a matrix or a data frame, with each row representing a random vector.

v

The vectors corresponding to the dataset. Should be a matrix or a data frame with the same shape as d. If missing, then the vectors will be calculated from the dataset.

h

The bandwidth for the kernel estimator.

kernel

The type of kernel estimator used. "exp" by default (exp()), and if "Gaussian" then stats::dnorm() will be used.

Value

A function(x), which then returns the \(\mu\) and \(a\) estimators at the position \(x\).

References

Bandi, F. M., & Moloche, G. (2018). On the functional estimation of multivariate diffusion processes. Econometric Theory, 34(4), 896-946. https://doi.org/10.1017/S0266466617000305