correlation {SciViews} | R Documentation |
Correlation matrices.
Description
Compute the correlation matrix between two variables, or more (between all columns of a matrix or data frame).
Usage
correlation(x, ...)
Correlation(x, ...)
## S3 method for class 'formula'
correlation(formula, data = NULL, subset, na.action, ...)
## Default S3 method:
correlation(x, y = NULL, use = "everything",
method = c("pearson", "kendall", "spearman"), ...)
is.Correlation(x)
is.correlation(x)
as.Correlation(x)
as.correlation(x)
## S3 method for class 'Correlation'
print(x, digits = 3, cutoff = 0, ...)
## S3 method for class 'Correlation'
summary(object, cutpoints = c(0.3, 0.6, 0.8, 0.9, 0.95),
symbols = c(" ", ".", ",", "+", "*", "B"), ...)
## S3 method for class 'summary.Correlation'
print(x, ...)
## S3 method for class 'Correlation'
plot(x, y = NULL, outline = TRUE, cutpoints = c(0.3,
0.6, 0.8, 0.9, 0.95), palette = rwb.colors, col = NULL, numbers = TRUE,
digits = 2, type = c("full", "lower", "upper"), diag = (type == "full"),
cex.lab = par("cex.lab"), cex = 0.75 * par("cex"), ...)
## S3 method for class 'Correlation'
lines(x, choices = 1L:2L, col = par("col"), lty = 2,
ar.length = 0.1, pos = NULL, cex = par("cex"), labels = rownames(x),
...)
Arguments
x |
A numeric vector, matrix or data frame (or any object for
|
... |
Further arguments passed to functions. |
formula |
A formula with no response variable, referring only to numeric variables. |
data |
An optional data frame (or similar: see |
subset |
An optional vector used to select rows (observations) of the
data matrix |
na.action |
A function which indicates what should happen when the data
contain |
y |
|
use |
An optional character string giving a method for computing
correlations in the presence of missing values. This must be (an abbreviation
of) one of the strings |
method |
A character string indicating which correlation coefficient is
to be computed. One of |
digits |
Digits to print after the decimal separator. |
cutoff |
Correlation coefficients lower than this (in absolute value) are suppressed. |
object |
A 'Correlation' object. |
cutpoints |
The cut points to use for categories. Specify only positive values (absolute value of correlation coefficients are summarized, or negative equivalents are automatically computed for the graph. Do not include 0 or 1 in the cutpoints). |
symbols |
The symbols to use to summarize the correlation matrix. |
outline |
Do we draw the outline of the ellipse? |
palette |
A function that can produce a palette of colors. |
col |
Color of the ellipse. If |
numbers |
Do we print correlation values in the center of the ellipses? |
type |
Do we plot a complete matrix, or only lower or upper triangle? |
diag |
Do we plot items on the diagonal? They have always a correlation of one. |
cex.lab |
The expansion factor for labels. |
cex |
The expansion factor for text. |
choices |
The items to select |
lty |
The line type to draw. |
ar.length |
The length of the arrow head. |
pos |
The position relative to arrows. |
labels |
The label to draw nead arrows. |
Value
Correlation()
and as.Correlation()`` create a 'Correlation' object, while
is.Correlation()“ tests for it.
There are print()
and summary()
methods for the 'Correlation' object
that differ in the symbolic encoding of the correlations in summary()
,
using5 symnum()], which makes large correlation matrices more readable.
The method plot()
returns nothing, but it draws ellipses on a graph that
represent the correlation matrix visually. This is essentially the
plotcorr()
function from package ellipse, with slightly different
default arguments and with default cutpoints
equivalent to those used in
the summary()
method.
Author(s)
Philippe Grosjean phgrosjean@sciviews.org, wrapping code in package
ellipse, function plotcorr()
for the plot.Correlation()
method.
See Also
cov()
, cov2cor()
, cov.wt()
, symnum()
, plotcorr()
and look
at panel_cor()
Examples
# This is a simple correlation coefficient
cor(rnorm(10), runif(10))
Correlation(rnorm(10), runif(10))
# 'Correlation' objects allow better inspection of the correlation matrices
# than the output of default R cor() function
(longley.cor <- Correlation(longley))
summary(longley.cor) # Synthetic view of the correlation matrix
plot(longley.cor) # Graphical representation
# Use of the formula interface
(mtcars.cor <- Correlation(~ mpg + cyl + disp + hp, data = mtcars,
method = "spearman", na.action = "na.omit"))
mtcars.cor2 <- Correlation(mtcars, method = "spearman")
print(mtcars.cor2, cutoff = 0.6)
summary(mtcars.cor2)
plot(mtcars.cor2, type = "lower")
mtcars.cor2["mpg", "cyl"] # Extract a correlation from the correlation matrix