pca_examination: Principal Component Exploration

In fChange: Functional Change Point Detection and Analysis

Principal Component Exploration

Description

Computes the principal component projection and re-combined data with a myriad of figures to understand the projection process.

Usage

pca_examination(X, TVE = 0.95)

Arguments

X	A dfts object or data which can be automatically converted to that format. See dfts().
TVE	Numeric in [0,1] for the total variance explained, this determines the number of components and can be used for dimension reduction.

Value

List with the following elements:

• figures: List with figures on all components, summaries, reconstructed values, and residuals.

• reconstruction: Reconstructed value from PCs.

• residuals: Difference between true and reconstruction.

See Also

pca.dfts()

Examples

results <- pca_examination(electricity, TVE = 0.9)

fChange documentation built on June 21, 2025, 9:08 a.m.