LOOCV_grid: LOOCV Leave-one-out cross-validation
In hoangtt1989/NOIS: Non-parametric Outlier Identification and Smoothing
Description
Usage
Arguments
Value
See Also
Description
Evaluate leave-one-out cross-validation (LOOCV) for the Nadaraya-Watson estimator over a grid
Usage
1
2
LOOCV_grid(x, y, hgrid = seq(from = 0.05, to = 3, length.out = 80),
weight_probs = c(0.05, 0.95))
Arguments
x
'x' values.
y
'y' values.
hgrid
The grid of test bandwidths.
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: MCV_grid,
NOIS_fit, PCV_grid
hoangtt1989/NOIS documentation built on May 20, 2019, 2:08 p.m.
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Description Usage Arguments Value See Also
Description
Evaluate leave-one-out cross-validation (LOOCV) for the Nadaraya-Watson estimator over a grid
Usage
1 2 | LOOCV_grid(x, y, hgrid = seq(from = 0.05, to = 3, length.out = 80),
weight_probs = c(0.05, 0.95))
|
Arguments
x |
'x' values. |
y |
'y' values. |
hgrid |
The grid of test bandwidths. |
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: MCV_grid,
NOIS_fit, PCV_grid
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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