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factoextra (version 1.0.3)

fviz_hmfa: Visualize Hierarchical Multiple Factor Analysis

Description

Graph of individuals/quantitative variables/qualitative variables/group/partial axes from the output of Hierarchical Multiple Factor Analysis (HMFA).
  • fviz_hmfa_ind(): Graph of individuals
  • fviz_hmfa_ind_starplot(): Graph of partial individuals
  • fviz_hmfa_quanti_var(): Graph of quantitative variables
  • fviz_hmfa_quali_var(): Graph of qualitative variables
  • fviz_hmfa_quali_biplot(): Biplot of individuals and qualitative variables
  • fviz_hmfa_group(): Graph of the groups representation
  • fviz_hmfa(): An alias of fviz_hmfa_ind()

Usage

fviz_hmfa_ind(X, axes = c(1, 2), geom = c("point", "text"), label = "all", invisible = "none", labelsize = 4, pointsize = 2, habillage = "none", addEllipses = FALSE, ellipse.level = 0.95, ellipse.type = "norm", ellipse.alpha = 0.1, col.ind = "blue", col.ind.sup = "darkblue", alpha.ind = 1, shape.ind = 19, repel = FALSE, axes.linetype = "dashed", select.ind = list(name = NULL, cos2 = NULL, contrib = NULL), title = "Individuals factor map - HMFA", jitter = list(what = "label", width = NULL, height = NULL), ...)


fviz_hmfa_quanti_var(X, axes = c(1, 2), geom = c("arrow", "text"), label = "all", invisible = "none", labelsize = 4, pointsize = 2, col.var = "red", alpha.var = 1, shape.var = 17, col.quanti.sup = "blue", col.quali.sup = "darkgreen", col.circle = "grey70", select.var = list(name = NULL, cos2 = NULL, contrib  = NULL), axes.linetype = "dashed", title = "Quantitative Variable categories - MFA", repel = FALSE, jitter = list(what = "label", width = NULL, height = NULL))


fviz_hmfa_quali_var(X, axes = c(1, 2), geom = c("point", "text"), label = "all", invisible = "none", labelsize = 4, pointsize = 2, col.var = "red", alpha.var = 1, shape.var = 17, col.quanti.sup = "blue", col.quali.sup = "darkgreen", repel = FALSE, select.var = list(name = NULL, cos2 = NULL, contrib = NULL), axes.linetype = "dashed", title = "Qualitative Variable categories - MFA", jitter = list(what = "label", width = NULL, height = NULL))


fviz_hmfa_quali_biplot(X, axes = c(1, 2), geom = c("point", "text"), label = "all", invisible = "none", labelsize = 4, pointsize = 2, habillage = "none", addEllipses = FALSE, ellipse.level = 0.95, col.ind = "blue", col.ind.sup = "darkblue", alpha.ind = 1, col.var = "red", alpha.var = 1, col.quanti.sup = "blue", col.quali.sup = "darkgreen", axes.linetype = "dashed", shape.ind = 19, shape.var = 17, select.var = list(name = NULL, cos2 = NULL, contrib = NULL), select.ind = list(name = NULL, cos2 = NULL, contrib = NULL), arrows = c(FALSE, FALSE), repel = FALSE, title = "HMFA factor map - Biplot", jitter = list(what = "label", width = NULL, height = NULL), ...)


fviz_hmfa_ind_starplot(X, axes = c(1, 2), geom = c("point", "text"), group.names = NULL, label = "all", invisible = "none", legend.partial.title = NULL, labelsize = 4, pointsize = 2, linesize = 0.5, repel = FALSE, habillage = "none", addEllipses = FALSE, ellipse.level = 0.95, ellipse.type = "norm", ellipse.alpha = 0.1, col.ind = "black", col.ind.sup = "darkblue", col.partial = "black", alpha.ind = 1, shape.ind = 19, alpha.partial = 1, node.level = 1, select.ind = list(name = NULL, cos2 = NULL, contrib = NULL), select.partial = list(name = NULL, cos2 = NULL, contrib = NULL), axes.linetype = "dashed", title = "Individuals factor map - MFA", jitter = list(what = "label", width = NULL, height = NULL), ...)


fviz_hmfa_group(X, axes = c(1, 2), geom = c("point", "text"), alpha.group = 1, shape.group = 17, label = "all", invisible = "none", labelsize = 4, pointsize = 2, col.group = "blue", col.group.sup = "darkgreen", repel = FALSE, select.group = list(name = NULL, cos2 = NULL, contrib = NULL), title = "MFA - Groups Representations", jitter = list(what = "label", width = NULL, height = NULL), ...)


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 both types.
label
a text specifying the elements to be labelled. Default value is "all". Allowed values are "none" or the combination of c("ind", "ind.sup","var", "quali.sup", "quanti.sup"). "ind" can be used to label only active individuals. "ind.sup" is for supplementary individuals. "var" is for active variable categories. "quali.sup" is for supplementary qualitative variable categories. "quanti.sup" is for quantitative supplementary variables.
invisible
a text specifying the elements to be hidden on the plot. Default value is "none". Allowed values are the combination of c("ind", "ind.sup","var", "quali.sup", "quanti.sup").
labelsize
font size for the labels
pointsize
the size of points
habillage
an optional factor variable for coloring the observations by groups. Default value is "none". If X is an MFA 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".
ellipse.level
the size of the concentration ellipse in normal probability.
ellipse.type
Character specifying frame type. Possible values are 'convex' or types supporeted by stat_ellipse including one of c("t", "norm", "euclid").
ellipse.alpha
Alpha for ellipse specifying the transparency level of fill color. Use alpha = 0 for no fill color.
col.ind, col.partial, col.var, col.group
color for individuals, partial individuals, variables, groups and axes, respectively. Possible values include also : "cos2", "contrib", "coord", "x" or "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.partial, alpha.var, alpha.group
controls the transparency of individual, partial individual, variable, group and axes colors, respectively. The value can variate from 0 (total transparency) to 1 (no transparency). Default value is 1. Possible values include also : "cos2", "contrib", "coord", "x" or "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".
shape.ind, shape.var, shape.group
point shapes of individuals, variables, groups and axes
repel
a boolean, whether to use ggrepel to avoid overplotting text labels or not.
axes.linetype
linetype of x and y axes.
select.ind, select.partial, select.var, select.group
a selection of individuals/partial individuals/ variables/groups/axes 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 cos2 are drawn
title
the title of the graph
jitter
a parameter used to jitter the points in order to reduce overplotting. It's a list containing the objects what, width and height (i.e jitter = list(what, width, height)).
  • what: the element to be jittered. Possible values are "point" or "p"; "label" or "l"; "both" or "b"
  • width: degree of jitter in x direction
  • height: degree of jitter in y direction
...
Arguments to be passed to the function fviz_mfa_quali_biplot()
col.quanti.sup, col.quali.sup, col.group.sup
a color for the quantitative/qualitative supplementary variables.
col.circle
a color for the correlation circle.
arrows
Vector of two logicals specifying if the plot should contain points (FALSE, default) or arrows (TRUE). First value sets the rows and the second value sets the columns.
group.names
a vector containing the name of the groups (by default, NULL and the group are named group.1, group.2 and so on).
legend.partial.title
the title of the partal groups legend.
linesize
size of partial point connecting line.
node.level
a single number indicating the HMFA node level to plot.

Value

a ggplot2 plot

References

http://www.sthda.com

Examples

Run this code
# 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
# ++++++++++++++++++++
# Default plot
# 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")

## Not run: 
# # 1. Control automatically the color of individuals 
#    # using the "cos2" or the contributions "contrib"
#    # cos2 = the quality of the individuals on the factor map
# # 2. To keep only point or text use geom = "point" or geom = "text".
# # 3. Change themes: http://www.sthda.com/english/wiki/ggplot2-themes
# 
# fviz_hmfa_ind(res.hmfa, col.ind="cos2")+
# theme_minimal()
# ## End(Not run)

# Color individuals by groups, add concentration ellipses
# Remove labels: label = "none".
grp <- as.factor(wine[,1])
p <- fviz_hmfa_ind(res.hmfa, label="none", habillage=grp,
       addEllipses=TRUE, ellipse.level=0.95)+
       theme_minimal()
print(p)

## Not run: 
# # Change group colors using RColorBrewer color palettes
# # Read more: http://www.sthda.com/english/wiki/ggplot2-colors
# p + scale_color_brewer(palette="Paired") +
#     scale_fill_brewer(palette="Paired") +
#      theme_minimal()
# ## End(Not run)
     
# Change group colors manually
# Read more: http://www.sthda.com/english/wiki/ggplot2-colors
p + scale_color_manual(values=c("#999999", "#E69F00", "#56B4E9"))+
 scale_fill_manual(values=c("#999999", "#E69F00", "#56B4E9"))+
 theme_minimal()  
   
## Not run: 
# # Select and visualize some individuals (ind) with select.ind argument.
#  # - ind with cos2 >= 0.1: select.ind = list(cos2 = 0.1)
#  # - Top 20 ind according to the cos2: select.ind = list(cos2 = 20)
#  # - Top 20 contributing individuals: select.ind = list(contrib = 20)
#  # - Select ind by names: select.ind = list(name = c("1VAU", "1FON") )
#  
# # Example: Select the top 10 according to the cos2
# fviz_hmfa_ind(res.hmfa, select.ind = list(cos2 = 100))
# ## End(Not run)


# Graph of qantitative variable categories
# ++++++++++++++++++++++++++++++++++++++++
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)

# Plot
# Control variable colors using their contributions
fviz_hmfa_quanti_var(res.hmfa, col.var = "contrib")+
 scale_color_gradient2(low = "white", mid = "blue",
           high = "red", midpoint = 12) +
 theme_minimal()

## Not run: 
# # Select variables with select.var argument
#    # You can select by contrib, cos2 and name 
#    # as previously described for ind
# # Select the top 10 contributing variables
# fviz_hmfa_quanti_var(res.hmfa, select.var = list(contrib = 10))
# ## End(Not run)
 
# Graph of categorical variable categories
# ++++++++++++++++++++++++++++++++++++++++
data(poison)
hierar <- list(c(2,2,5,6), c(1,3))
res.hmfa <- HMFA(poison, H = hierar, type=c("s","n","n","n"), graph = FALSE)

# Default plot
fviz_hmfa_quali_var(res.hmfa, col.var = "contrib")+
 theme_minimal()


# Biplot of categorical variable categories and individuals
# +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
grp <- as.factor(poison[, "Vomiting"])
# Use repel = TRUE to avoid overplotting
fviz_hmfa_quali_biplot(res.hmfa, col.var = "#E7B800", repel = FALSE,
    habillage = grp, addEllipses = TRUE)+ 
theme_minimal()

               
# Graph of partial individuals (starplot)
# +++++++++++++++++++++++++++++++++++++++
fviz_hmfa_ind_starplot(res.hmfa, col.partial = "group.name")+
scale_color_brewer(palette = "Dark2") 
 theme_minimal()
 
 
## Not run: 
# # Select the partial points of the top 5
# # contributing individuals
# fviz_hmfa_ind_starplot(res.hmfa, 
#                       select.partial = list(contrib = 2))+
#                       theme_minimal()
#                       
# # Change colours of star segments
# fviz_hmfa_ind_starplot(res.hmfa, select.partial = list(contrib = 5), 
#                       col.partial = "group.name") +
#                       scale_color_brewer(palette = "Dark2") +
#                       theme_minimal()
#  ## End(Not run)
  
  
# Graph of groups (correlation square)
# ++++++++++++++++++++++++++++++++++++
fviz_hmfa_group(res.hmfa)

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