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Visualize Hierarchical Multiple Factor Analysis

Source: R/fviz_hmfa.R
fviz_hmfa.Rd

Hierarchical Multiple Factor Analysis (HMFA) is an extension of MFA, used in a situation where the data are organized into a hierarchical structure. fviz_hmfa() provides ggplot2-based elegant visualization of HMFA outputs from the R function: HMFA [FactoMineR].

  • fviz_hmfa_ind(): Graph of individuals

  • fviz_hmfa_var(): Graph of variables

  • fviz_hmfa_quali_biplot(): Biplot of individuals and qualitative variables

  • fviz_hmfa(): An alias of fviz_hmfa_ind()

Read more: Multiple Factor Analysis (MFA) in R: Analyze Groups of Variables.

Usage

fviz_hmfa_ind(
  X,
  axes = c(1, 2),
  geom = c("point", "text"),
  repel = FALSE,
  habillage = "none",
  addEllipses = FALSE,
  shape.ind = 19,
  col.ind = "blue",
  col.ind.sup = "darkblue",
  alpha.ind = 1,
  select.ind = list(name = NULL, cos2 = NULL, contrib = NULL),
  partial = NULL,
  col.partial = "group",
  group.names = NULL,
  node.level = 1,
  ...
)

fviz_hmfa_var(
  X,
  choice = c("quanti.var", "quali.var", "group"),
  axes = c(1, 2),
  geom = c("point", "text"),
  repel = FALSE,
  col.var = "red",
  alpha.var = 1,
  shape.var = 17,
  col.var.sup = "darkgreen",
  select.var = list(name = NULL, cos2 = NULL, contrib = NULL),
  ...
)

fviz_hmfa_quali_biplot(
  X,
  axes = c(1, 2),
  geom = c("point", "text"),
  repel = FALSE,
  habillage = "none",
  title = "Biplot of individuals and qualitative variables - HMFA",
  ...
)

fviz_hmfa(X, ...)

Arguments

X

an object of class HMFA [FactoMineR].

axes

a numeric vector of length 2 specifying the dimensions to be plotted.

geom

a text specifying the geometry to be used for the graph. Allowed values are the combination of c("point", "arrow", "text"). Use "point" (to show only points); "text" to show only labels; c("point", "text") or c("arrow", "text") to show arrows and texts. Using c("arrow", "text") is sensible only for the graph of variables.

repel

logical; whether to use ggrepel to avoid overplotting text labels. The old jitter argument is kept for backward compatibility and is converted to repel = TRUE with a deprecation warning.

habillage

an optional factor variable for coloring the observations by groups. Default value is "none". If X is an HMFA object from FactoMineR package, habillage can also specify the index of the factor variable in the data.

addEllipses

logical value. If TRUE, draws ellipses around the individuals when habillage != "none".

shape.ind, shape.var

point shapes of individuals and variables, respectively.

col.ind, col.var

color for individuals, partial individuals and variables, respectively. Can be a continuous variable or a factor variable. Possible values also include "cos2", "contrib", "coord", "x", and "y". In this case, the colors for individuals/variables are automatically controlled by their qualities ("cos2"), contributions ("contrib"), coordinates (x^2 + y^2 , "coord"), x values("x") or y values("y"). To use automatic coloring (by cos2, contrib, ....), make sure that habillage ="none".

col.ind.sup

color for supplementary individuals

alpha.ind, alpha.var

controls the transparency of individual, partial individual and variable, respectively. The value can vary from 0 (total transparency) to 1 (no transparency). Default value is 1. Possible values also include "cos2", "contrib", "coord", "x", and "y". In this case, the transparency for individual/variable colors are automatically controlled by their qualities ("cos2"), contributions ("contrib"), coordinates (x^2 + y^2 , "coord"), x values("x") or y values("y"). To use this, make sure that habillage ="none".

select.ind, select.var

a selection of individuals and variables to be drawn. Allowed values are NULL or a list containing the arguments name, cos2 or contrib:

  • name is a character vector containing individuals/variables to be drawn

  • cos2 if cos2 is in [0, 1], ex: 0.6, then individuals/variables with a cos2 > 0.6 are drawn. if cos2 > 1, ex: 5, then the top 5 individuals/variables with the highest cos2 are drawn.

  • contrib if contrib > 1, ex: 5, then the top 5 individuals/variables with the highest contributions are drawn

  • union: logical. When several of name/cos2/contrib are given, FALSE (default) combines them with AND (each condition further narrows the selection); TRUE combines them with OR (an element is kept if it matches any condition), e.g. named items plus the top-cos2 ones.

partial

list of the individuals for which the partial points should be drawn. (by default, partial = NULL and no partial points are drawn). Use partial = "all" to visualize partial points for all individuals.

col.partial

color for partial individuals. By default, points are colored according to the groups.

group.names

a vector containing the name of the groups (by default, NULL and the groups are named group.1, group.2, and so on).

node.level

a single number indicating the HMFA node level to plot.

...

Arguments to be passed to the function fviz() and ggpubr::ggpar()

choice

the graph to plot. Allowed values include one of c("quanti.var", "quali.var", "group") for plotting quantitative variables, qualitative variables and group of variables, respectively.

col.var.sup

color for supplementary variables.

title

the title of the graph

Value

a ggplot

References

https://www.datanovia.com/learn/

See also

get_hmfa, fviz_mfa. Online tutorial: Multiple Factor Analysis (MFA) in R: Analyze Groups of Variables.

Author

Fabian Mundt f.mundt@inventionate.de

Alboukadel Kassambara alboukadel.kassambara@gmail.com

Examples

# Hierarchical Multiple Factor Analysis
# ++++++++++++++++++++++++
# Install and load FactoMineR to compute MFA
# install.packages("FactoMineR")
library("FactoMineR")
data(wine)
hierar <- list(c(2,5,3,10,9,2), c(4,2))
res.hmfa <- HMFA(wine, H = hierar, type=c("n",rep("s",5)), graph = FALSE)

# Graph of individuals
# ++++++++++++++++++++
# Color of individuals: col.ind = "#2E9FDF"
# Use repel = TRUE to avoid overplotting (slow if many points)
fviz_hmfa_ind(res.hmfa, repel = TRUE, col.ind = "#2E9FDF")


# Color individuals by groups, add concentration ellipses
# Remove labels: label = "none".
# Change color palette to "jco". See ?ggpubr::ggpar
grp <- as.factor(wine[,1])
p <- fviz_hmfa_ind(res.hmfa, label="none", habillage=grp,
       addEllipses=TRUE, palette = "jco")
print(p)

 

# Graph of variables
# ++++++++++++++++++++++++++++++++++++++++
# Quantitative variables
fviz_hmfa_var(res.hmfa, "quanti.var")

# Graph of categorical variable categories
fviz_hmfa_var(res.hmfa, "quali.var")

# Groups of variables (correlation square)
fviz_hmfa_var(res.hmfa, "group")



# Biplot of categorical variable categories and individuals
# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
fviz_hmfa_quali_biplot(res.hmfa)

    
# Graph of partial individuals (starplot)
# +++++++++++++++++++++++++++++++++++++++
fviz_hmfa_ind(res.hmfa, partial = "all", col.partial = "black")
#> Ignoring unknown labels:
#> • colour : "Groups"