plot_correlations | R Documentation |
Function to plot either a) the upper triangle component of a correlation matrix, or b) a panel of correlations (e.g., between raw and component scores from a PCA, between predictors and different outcomes, etc.).
plot_correlations(
dtf = NULL,
R = NULL,
n = NULL,
p_values = NULL,
labels = NULL,
label_pos = c(0.2, 0.25),
only_upper_tri = TRUE,
new = TRUE,
width = 5,
height = 5,
margin = NULL,
fill = c("#E69F00", "#56B4E9"),
opaque = 0.4,
cex = c(0.8, 0.8),
value = TRUE,
digits = 2,
method = "BH",
alpha = 0.05,
legend_pos = c(0, 0.5, 0)
)
dtf |
A data frame, a set of variables to compute a correlation matrix over. |
R |
A matrix of correlations (must be supplied
if |
n |
An integer, the sample size for the correlations
(computed automatically if |
p_values |
A matrix of p-values (must have same dimensions
as |
labels |
Either a character vector with the labels for the rows of the correlation matrix, or a list of character vectors with the labels for the rows and columns, respectively, for the correlation matrix. |
label_pos |
A numeric vector the x-axis adjustment for row labels and the y-axis adjustment for column labels, respectively. |
only_upper_tri |
A logical value, |
new |
A logical value; if |
width |
An integer value, the width in inches of the plot. |
height |
An integer value, the height in inches of the plot. |
margin |
A numeric vector, four values specifying the margins of the plot in inches, giving the spacing for the bottom, left, top, and right sides respectively. |
fill |
A character vector, the colors for negative and positive correlations respectively. |
opaque |
A numeric value ranging from 0 to 1, with lower values indicating greater translucency of the fill color. |
cex |
A numeric vector of two values, the text size for the row/column labels and correlation values, respectively. |
digits |
An integer value, the number of digits to round correlation values to. |
method |
A character string, the method to use for multiple comparison adjustment (see stats::p.adjust). |
alpha |
A numeric value between 0 and 1, the cut-off for statistical significance (default is 0.05). |
legend_pos |
A numeric vector of 3 values governing the y-axis position and x-axis positions, respectively, for the legend. |
A plot of the correlations.
# Correlation matrix
data(mtcars)
plot_correlations( dtf = mtcars, new = FALSE )
# Example based on PCA
# Loading matrix
lambda <- cbind(
c( runif( 4, .3, .9 ), rep( 0, 4 ) ),
c( rep( 0, 4 ), runif( 4, .3, .9 ) )
)
# Communalities
D_tau <- diag( runif( 8, .5, 1.5 ) )
cov_mat <- lambda %*% t( lambda ) + D_tau
cor_mat <- cov2cor( cov_mat )
set.seed( 341 ) # For reproducibility
x <- MASS::mvrnorm( n = 200, mu = rep( 0, 8 ), Sigma = cor_mat )
colnames(x) <- paste0( 'C', 1:8 )
PCA <- principal_components_analysis( x )
# Correlations between raw variables
# and component scores from PCA
plot_correlations(
R = PCA$Correlations$Train[, 1:2], n = 200,
labels = list(
paste0( 'Variable ', 1:8 ),
paste0( 'Comp. ', 1:2 )
),
only_upper_tri = F, margin = c( .25, 2, .25, .25 ),
legend_pos = c( 0, 0, -.25 ),
new = FALSE
)
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