Description Usage Arguments Value Author(s) References See Also Examples
This function is designed to point out the variables and the categories that are the most characteristic according
to each dimension obtained by a Factor Analysis.
1 | dimdesc(res, axes = 1:3, proba = 0.05)
|
res |
an object of class PCA, MCA, CA, MFA or HMFA |
axes |
a vector with the dimensions to describe |
proba |
the significance threshold considered to characterized the dimension (by default 0.05) |
Returns a list including:
quanti |
the description of the dimensions by the quantitative variables. The variables are sorted. |
quali |
the description of the dimensions by the categorical variables |
Francois Husson [email protected]
Husson, F., Le, S. and Pages, J. (2010). Exploratory Multivariate Analysis by Example Using R, Chapman and Hall.
PCA
, CA
, MCA
, MFA
, HMFA
,
Video showing how to use this function
1 2 3 |
$Dim.1
$Dim.1$quanti
correlation p.value
Points 0.9561543 2.099191e-22
Long.jump 0.7418997 2.849886e-08
Shot.put 0.6225026 1.388321e-05
High.jump 0.5719453 9.362285e-05
Discus 0.5524665 1.802220e-04
Rank -0.6705104 1.616348e-06
400m -0.6796099 1.028175e-06
110m.hurdle -0.7462453 2.136962e-08
100m -0.7747198 2.778467e-09
$Dim.2
$Dim.2$quanti
correlation p.value
Discus 0.6063134 2.650745e-05
Shot.put 0.5983033 3.603567e-05
400m 0.5694378 1.020941e-04
1500m 0.4742238 1.734405e-03
High.jump 0.3502936 2.475025e-02
Javeline 0.3169891 4.344974e-02
Long.jump -0.3454213 2.696969e-02
$Dim.3
$Dim.3$quanti
correlation p.value
1500m 0.7821428 1.554450e-09
Pole.vault 0.6917567 5.480172e-07
Javeline -0.3896554 1.179331e-02
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