PCAy: Revised PCA analysis

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

Revised PCA analysis

Description

It's a revised PCA analysis.

Usage

PCAy(data)

Arguments

data	Numeric. Data matrix for revised PCA analysis.

Value

An object of class "PCAyd".

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

Sepal.Length<-c(4.8, 5.1, 4.6, 5.3, 5.0, 5.7, 5.7, 6.2, 5.1, 5.7, 6.7, 6.3,
 6.5, 6.2, 5.9)
Sepal.Width<-c(3.0, 3.8, 3.2, 3.7, 3.3, 3.0, 2.9, 2.9, 2.5, 2.8, 3.0, 2.5,
 3.0, 3.4, 3.0)
Petal.Length<-c(1.4, 1.6, 1.4, 1.5, 1.4, 4.2, 4.2, 4.3, 3.0, 4.1, 5.2, 5.0,
 5.2, 5.4, 5.1)
Petal.Width<-c(0.3, 0.2, 0.2, 0.2, 0.2, 1.2, 1.3, 1.3, 1.1, 1.3, 2.3, 1.9,
 2.0, 2.3, 1.8)
dat<-cbind(Sepal.Length,Sepal.Width,Petal.Length,Petal.Width)
Res<-PCAy(dat)

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