PCV_grid: Partitioned cross-validation

Description Usage Arguments Value See Also

Description

Evaluate partitioned cross-validation (PCV) for the Nadaraya-Watson estimator over a grid

Usage

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PCV_grid(x, y, hgrid = seq(from = 0.05, to = 3, length.out = 100),
  g = floor(length(x)/5), weight_probs = c(0.05, 0.95))

Arguments

x

'x' values.

y

'y' values.

hgrid

The grid of test bandwidths.

g

The number of points used in each training subgroup. This is the most sensitive parameter.

weight_probs

Specification for what percentage of points are used in the weight function.

Value

The minimum bandwidth h, the minimum CV error and the grid of test bandwidths.

See Also

Other NOIS CV functions: LOOCV_grid, MCV_grid, NOIS_fit


hoangtt1989/NOIS documentation built on May 20, 2019, 2:08 p.m.