Produces a network plot of a correlation matrix or an object computed with
corr_coef()
. Variables that are more highly correlated appear closer
together and are joined by stronger (more opaque) and wider paths. The proximity of the
points is determined using multidimensional clustering, also known as
principal coordinates analysis (Gower, 1966). The color of the paths also
indicates the sign of the correlation (blue for positive and red for
negative).
network_plot(
model,
min_cor = NULL,
show = c("signif", "all"),
p_val = 0.05,
legend = c("full", "range"),
colours = c("red", "white", "blue"),
legend_width = 1,
legend_height = 15,
legend_position = c("right", "left", "top", "bottom"),
curved = TRUE,
angle = 90,
curvature = 0.5,
expand_x = 0.25,
expand_y = 0.25
)
A ggplot
object
A model computed with corr_coef()
or a symmetric matrix, often
produced with stats::cor()
.
Number to indicate the minimum value of correlations to plot
(0-1 in absolute terms). By default, all the correlations are plotted when
model
is a matrix, and significant correlations (p-value < 0.05) when
model
is an object computed with corr_coef()
.
The correlations to be shown when model
is an object computed
with corr_coef()
. Either "signif"
(default) to show only significant
correlations or "all"
to show all the correlations.
The p-value to indicate significant correlations. Defaults to
0.05
.
The type of legend. Either "full"
(ranges from -1 to +1) or
"range"
(ranges according to the data range). Defaults to "full"
.
A vector of colors to use for n-color gradient.
The width of the legend (considering position = "right"
)
The height of the legend (considering position = "right"
)
The legend position. Defaults to "right"
.
Shows curved paths? Defaults to TRUE
.
A numeric value between 0 and 180, giving an amount to skew the control points of the curve. Values less than 90 skew the curve towards the start point and values greater than 90 skew the curve towards the end point.
A numeric value giving the amount of curvature. Negative values produce left-hand curves, positive values produce right-hand curves, and zero produces a straight line.
Vector of multiplicative range expansion factors. If
length 1, both the lower and upper limits of the scale are expanded
outwards by mult. If length 2, the lower limit is expanded by mult[1]
and
the upper limit by mult[2]
.
Gower, J.C. 1966. Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis. Biometrika 53(3/4): 325–338. tools:::Rd_expr_doi("10.2307/2333639")
cor <- corr_coef(iris)
network_plot(cor)
network_plot(cor,
show = "all",
curved = FALSE,
legend_position = "bottom",
legend = "range")
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