Description Usage Arguments Details Value Author(s) References See Also Examples
A faster, one-step calculation of Student correlation p-values for multiple correlations, properly taking into account the actual number of observations.
1 2 3 4  | corAndPvalue(x, y = NULL, 
             use = "pairwise.complete.obs", 
             alternative = c("two.sided", "less", "greater"),
             ...)
 | 
x | 
 a vector or a matrix  | 
y | 
 a vector or a matrix. If   | 
use | 
 determines handling of missing data. See   | 
alternative | 
 specifies the alternative hypothesis and must be (a unique abbreviation of) one of
  | 
... | 
 other arguments to the function   | 
The function calculates correlations of a matrix or of two matrices and the corresponding Student p-values.
The output is not as full-featured as cor.test, but can work with matrices as input.
A list with the following components, each a matrix:
cor | 
 the calculated correlations  | 
p | 
 the Student p-values corresponding to the calculated correlations  | 
Z | 
 Fisher transforms of the calculated correlations  | 
t | 
 Student t statistics of the calculated correlations  | 
nObs | 
 Numbers of observations for the correlation, p-values etc.  | 
Peter Langfelder and Steve Horvath
Peter Langfelder, Steve Horvath (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering. Journal of Statistical Software, 46(11), 1-17. http://www.jstatsoft.org/v46/i11/
cor for calculation of correlations only;
cor.test for another function for significance test of correlations
1 2 3 4 5 6 7 8 9 10 11  | # generate random data with non-zero correlation
set.seed(1);
a = rnorm(100);
b = rnorm(100) + a;
x = cbind(a, b);
# Call the function and display all results
corAndPvalue(x)
# Set some components to NA
x[c(1:4), 1] = NA
corAndPvalue(x)
# Note that changed number of observations.
 | 
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