PCAyd-class: Class to contain the results from revised PCA analysis.

In SKNN: A Super K-Nearest Neighbor (SKNN) Classification Algorithm

Class to contain the results from revised PCA analysis.

Description

The function PCAy returns object of class PCAyd.

Objects from the Class

new("PCAyd",Var=new("numeric"),PC=new("matrix"),Scores=new("matrix"),IScores=new("numeric"))

Slots

Var:

An numeric vector giving the variance of each PC.

PC:

A numeric matrix about the coefficients of each PC.

Scores:

A numeric matrix showing the loading coefficiens of each PC.

IScores:

A numeric vector with each element being the rowsum of Scores.

Author(s)

Yarong Yang and Yoram Rubin

References

Yarong Yang, Matt Over, and Yoram Rubin.(2012) Strategic Placement of Localization Devices (such as Pilot Points and Anchors) in Inverse Modeling Schemes. Water Resources Research, 48, W08519, doi:10.1029/2012WR011864.

Yarong Yang, Nader Ebrahimi, and Yoram Rubin.(2024) SKNN: A Super K-Nearest Neighbor Classification Algorithm.

Examples

showClass("PCAyd")

SKNN documentation built on Oct. 9, 2024, 1:08 a.m.