4/3/2022

R Biplot Pca

Plot Pca In R
Pca Plot Interpretation
R Biplot Pca Program

biplot.princomp {stats}

R Documentation

A principal component analysis (PCA) is performed using the built-in R function prcomp and iris data. Fvizpcabiplot: Biplot of individuals of variables. Jun 18, 2018 In summary: A PCA biplot shows both PC scores of samples (dots) and loadings of variables (vectors). The further away these vectors are from a PC origin, the more influence they have on that PC. The further away these vectors are from a PC origin, the more influence they have on that PC.

Plotting PCA results in R using FactoMineR and ggplot2 Timothy E. This is a tutorial on how to run a PCA using FactoMineR, and visualize the result using ggplot2.
May 13, 2020 A biplot allows to visualize how the samples relate to one another in PCA (which samples are similar and which are different) and simultaneously reveal how each variable contributes to each principal component.

Biplot for Principal Components

Description

Produces a biplot (in the strict sense) from the output ofprincomp or prcomp

Usage

Arguments

`x`	an object of class `'princomp'`.
`choices`	length 2 vector specifying the components to plot. Only the defaultis a biplot in the strict sense.
`scale`	The variables are scaled by `lambda ^ scale` and theobservations are scaled by `lambda ^ (1-scale)` where`lambda` are the singular values as computed by`princomp`. Normally `0 <= scale <= 1`, and a warningwill be issued if the specified `scale` is outside this range.
`pc.biplot`	If true, use what Gabriel (1971) refers to as a 'principal componentbiplot', with `lambda = 1` and observations scaled up by sqrt(n) andvariables scaled down by sqrt(n). Then inner products betweenvariables approximate covariances and distances between observationsapproximate Mahalanobis distance.
`...`	optional arguments to be passed to`biplot.default`.

Details

This is a method for the generic function biplot. There isconsiderable confusion over the precise definitions: those of theoriginal paper, Gabriel (1971), are followed here. Gabriel andOdoroff (1990) use the same definitions, but their plots actuallycorrespond to pc.biplot = TRUE.

Side Effects

a plot is produced on the current graphics device.

Plot Pca In R

References

Gabriel, K. R. (1971).The biplot graphical display of matrices with applications toprincipal component analysis.Biometrika, 58, 453–467.

Pca Plot Interpretation

Gabriel, K. R. and Odoroff, C. L. (1990).Biplots in biomedical research.Statistics in Medicine, 9, 469–485.

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