DRIP (version 2.3)

plot.Surface_Cluster_Parameters: Plot Parameter Selection Results in Surface Estimation

Description

Plot information about a clustering-based surface estimation parameter selection object.

Usage

# S3 method for Surface_Cluster_Parameters
plot(x, ...)

Value

A plot of (modified) cross-validation scores is produced.

Arguments

x

A clustering-based surface estimation parameter selection object.

...

Further arguments passed to or from other methods.

Author

Yicheng Kang

Details

Plot some information about a clustering-based surface estimation parameter selection object. In particular, it plots the cross-validation (no blur) or modified cross-validation (there is blur involved) scores against the specified bandwidth values.

References

Kang, Y., Mukherjee, P.S. and Qiu, P. (2018) "Efficient Blind Image Deblurring Using Nonparametric Regression and Local Pixel Clustering", Technometrics, 60(4), 522 -- 531, tools:::Rd_expr_doi("10.1080/00401706.2017.1415975").

Qiu, P. (2009) "Jump-Preserving Surface Reconstruction from Noisy Data", Annals of the Institute of Statistical Mathematics, 61, 715 -- 751, tools:::Rd_expr_doi("10.1007/s10463-007-0166-9").

See Also

surfaceCluster_bandwidth, print.Surface_Cluster_Parameters, summary.Surface_Cluster_Parameters

Examples

data(brain)
bandwidth_select <- surfaceCluster_bandwidth(image = brain,
    bandwidths = c(3:4), sig.level = .9995, blur = FALSE)
plot(bandwidth_select)