Create a correlation heat map for object of class corr_coef
# S3 method for corr_coef plot( x, type = "lower", diag = FALSE, reorder = TRUE, signif = "stars", caption = TRUE, digits.cor = 2, digits.pval = 3, col.low = "blue", col.mid = "white", col.high = "red", lab.x.position = NULL, lab.y.position = NULL, legend.position = NULL, legend.title = "Pearson's\nCorrelation", size.text.cor = 3, size.text.signif = 3, size.text.lab = 10, ... )
x | The data set. |
---|---|
type | The type of heat map to produce. Either |
diag | Plot diagonal elements? Defaults to |
reorder | Reorder the correlation matrix to identify the hidden pattern?
Defaults to |
signif | How to show significant correlations. If |
caption | Logical. If |
digits.cor, digits.pval | The significant digits to show for correlations and p-values, respectively. |
col.low, col.mid, col.high | The color for the low (-1), mid(0) and high
(1) points in the color key. Defaults to |
lab.x.position, lab.y.position | The position of the x and y axis label.
Defaults to |
legend.position | The legend position in the plot. |
legend.title | The title of the color key. Defaults to |
size.text.cor | The size of the text for correlation values. Defaults to 3. |
size.text.signif | The size of the text for significance values (stars or p-values). Defaults to 3. |
size.text.lab | The size of the text for labels. Defaults to 10. |
... | Currently not used. |
An object of class gg, ggplot
Tiago Olivoto tiagoolivoto@gmail.com
#> Warning: Removed 23 rows containing missing values (geom_text).#> Warning: Removed 23 rows containing missing values (geom_text).# Select variables sel <- corr_coef(data_ge2, EP, EL, CD, CL) plot(sel, type = "upper", reorder = FALSE, size.text.lab = 14, size.text.plot = 5)# }