What is Factoextra?

What is Factoextra?

factoextra is an R package making easy to extract and visualize the output of exploratory multivariate data analyses, including: Multiple Factor Analysis (MFA) dedicated to datasets where variables are organized into groups (qualitative and/or quantitative variables).

How do I install Ggfortify?

1. Installation. ggfortify can be installed from GitHub or CRAN: # Github if(!require(devtools)) install.packages(“devtools”) devtools::install_github(“sinhrks/ggfortify”) # CRAN install.packages(“ggfortify”)
2. Loading ggfortify. library(“ggfortify”)
3. Plotting matrix.
4. Plotting diagnostics for LM and GLM.
5. Plotting time series.

What is PC1 and PC2 select most appropriate?

Why typically PC1 vs. PC2. Simply because those axes (Principal Components) are ordered by the % of variability they explain, being PC1 always the axis that explain more variability among the samples included in the test. PC2 is the second axes expalaining more variability, and so on.

How is a principal component analysis ( PCA ) performed?

Arguments to be passed to the function fviz_pca_biplot (). A principal component analysis (PCA) is performed using the built-in R function prcomp () and iris data:

When to use habillage for PCA in FactoMineR?

If X is a PCA object from FactoMineR package, habillage can also specify the supplementary qualitative variable (by its index or name) to be used for coloring individuals by groups (see ?PCA in FactoMineR). logical value. If TRUE, draws ellipses around the individuals when habillage != “none”.

When to use C ( arrow, text ) in PCA?

Using c (“arrow”, “text”) is sensible only for the graph of variables. as geom but for individuals and variables, respectively. Default is geom.ind = c (“point”, “text), geom.var = c (“arrow”, “text”). a boolean, whether to use ggrepel to avoid overplotting text labels or not. an optional factor variable for coloring the observations by groups.

Which is the core function of fviz _ PCA?

Read more: Principal Component Analysis Note that, fviz_pca_xxx () functions are wrapper arround the core function fviz (), whih is also a wrapper arround the function ggscatter () [in ggpubr]. Therfore, further arguments, to be passed to the function fviz () and ggscatter (), can be specified in fviz_pca_ind () and fviz_pca_var ().