find_bws: Estimate bandwidths based on local likelihood...
In LAJordanger/localgaussSpec: Local Gaussian Spectral Analysis

Description Usage Arguments Details Value

View source: R/find_bws.R

Estimate bandwidths based on local likelihood...

1 2	find_bws(data, .kernel = c("normal", "uniform"), use_boundaries = TRUE, boundary_percentiles = c(0.1, 0.9), tol = 1e-04)

`data`	A matrix containing the multivariate observations, one observation in each row. Note that the marginals of these observations must be normalised in order for the assumptions of this code to be satisfied.
`.kernel`	Specification of the kernel to use, either `normal` or `uniform`, with default being the `normal` one if none is selected. Note: The `uniform`-kernel takes much longer to compute (a factor of ten when used on a small sample of size $n=200$).
`use_boundaries`	Logic value, default `TRUE`, that decides whether or not the bandwidths will be selected within the restrictions given by the argument `boundary_percentiles`
`boundary_percentiles`	A vector specifying two percentiles, default `c(0.1, 0.9)`, that will be used on the range of the individual margins in order to ensure that the returned bandwidths are within a "reasonable" range. This argument will be ignored when `use_boundaries` are given as `FALSE`.
`tol`	Convergence tolerance, default value `1e-04`. The iteration is terminated when the absolute difference in function value between successive iteration is below `tol`.

The defaults for this function has been selected after an investigation of how different settings affected the final values, with an emphasis on getting "good enough" values within a shortest possible computational time. Keep in mind that the data must have normalised marginals.

The result of this function is a matrix that for each bivariate combination from the points given in data will return the bandwidths obtained when the function link{find_rho} has been optimised with regard to the selected bivariate subset of the data. In addition to the bandwidths, there will also be a convergence-column that should contain 0 if the numerical combination of the bandwidths succeeded without any problems.

LAJordanger/localgaussSpec documentation built on July 28, 2017, 12:15 a.m.