print.Cluster: Print Parameter Selection Results in Surface Estimation

In DRIP: Discontinuous Regression and Image Processing

Print Parameter Selection Results in Surface Estimation

Description

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

Usage

## S3 method for class 'Surface_Cluster_Parameters'
print(x, type = "all", ...)

Arguments

x	A clustering-based surface estimation parameter selection object.
type	The type of information to display. The "cv_scores" option prints the cross-validation or modified cross-validation scores for each bandwidth. The "sigma" option prints the estimated noise level. The "phi0" option prints the estimated value of the error density at 0. The "mean_std_abs" option prints the estimated mean of absolute error. The "all" option prints all the information.
...	Further arguments passed to or from other methods.

Details

Prints some information about a clustering-based surface estimation parameter selection object. In particular, this method prints the cross- validation or modified cross-validation scores, the selected bandwidth, the estimated noise level, the estimated value of the error density at 0 and the estimated mean of absolute error.

Value

A display of parameter selection results in clustering-based surface estimation.

Author(s)

Yicheng Kang

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, \Sexpr[results=rd]{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, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1007/s10463-007-0166-9")}.

See Also

surfaceCluster_bandwidth, summary.Surface_Cluster_Parameters, plot.Surface_Cluster_Parameters

Examples

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

DRIP documentation built on April 4, 2025, 12:31 a.m.