basis_pca: The basis of Principal Component Analysis (PCA)

In spinifex: Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data

The basis of Principal Component Analysis (PCA)

Description

The orthogonal linear components of the variables in the next largest direction of variance.

Usage

basis_pca(data, d = 2)

Arguments

data	Numeric matrix or data.frame of the observations.
d	Number of dimensions in the projection space.

See Also

Rdimtools::do.pca

Other basis producing functions: basis_guided(), basis_half_circle(), basis_odp(), basis_olda(), basis_onpp()

Examples

dat <- scale_sd(wine[, 2:6])
basis_pca(data = dat)

spinifex documentation built on May 29, 2024, 1:23 a.m.