Rows contribution chart
This function allows to calculate the contribution of the row categories to the selected dimension.
rows.cntr( data, x = 1, categ.sort = TRUE, corr.thrs = 0, leg = TRUE, cex.labls = 0.75, dotprightm = 5, cex.leg = 0.6, leg.x.spc = 1, leg.y.spc = 1 )
data |
Name of the dataset (must be in dataframe format). |
x |
Dimension for which the row categories contribution is returned (1st dimension by default). |
categ.sort |
Logical value (TRUE/FALSE) which allows to sort the categories in descending order of contribution to the inertia of the selected dimension. TRUE is set by default. |
corr.thrs |
Threshold above which the column categories correlation will be displayed in the plot's legend. |
leg |
Enable (TRUE; default) or disable (FALSE) the legend at the right-hand side of the dot plot. |
cex.labls |
Adjust the size of the dot plot's labels. |
dotprightm |
Increases the empty space between the right margin of the dot plot and the left margin of the legend box. |
cex.leg |
Adjust the size of the legend's characters. |
leg.x.spc |
Adjust the horizontal space of the chart's legend. See more info from the 'legend' function's help (?legend). |
leg.y.spc |
Adjust the y interspace of the chart's legend. See more info from the 'legend' function's help (?legend). |
The function displays the contribution of the categories as a dot plot. A reference line indicates the threshold above which a contribution can be considered important for the determination of the selected dimension. The parameter categ.sort=TRUE sorts the categories in descending order of contribution to the inertia of the selected dimension. At the left-hand side of the plot, the categories' labels are given a symbol (+ or -) according to whether each category is actually contributing to the definition of the positive or negative side of the dimension, respectively. The categories are grouped into two groups: 'major' and 'minor' contributors to the inertia of the selected dimension. At the right-hand side, a legend (which is enabled/disabled using the 'leg' parameter) reports the correlation (sqrt(COS2)) of the column categories with the selected dimension. A symbol (+ or -) indicates with which side of the selected dimension each column category is correlated.
data(greenacre_data) #Plots the contribution of the row categories to the 2nd CA dimension, #and also displays the contribnution to the total inertia. #The categories are sorted in descending order of contribution to the inertia #of the selected dimension. rows.cntr(greenacre_data, 2, categ.sort=TRUE)
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