Rowwise Correlation with a Vector
Computes Pearson's correlation coefficient of a vector with each row of a matrix.
rowCors(X, y, trendStat = FALSE, use.n = NULL)
X |
a numeric matrix in which each row represents a variable and each column an observation. |
y |
a numeric vector of length |
trendStat |
instead of the correlation coefficients should the values of
the statistic for a test of linear trend based on this coefficient be returned?
If |
use.n |
should the squared values of the correlation coefficient be multiplied
by |
A vector containing the rowwise values of Pearson's correlation coefficient (if
trendStat = FALSE or the rowwise values of the trend statistics (if
trendStat = TRUE.
Holger Schwender, holger.schwender@udo.edu
Agresti, A.\ (2002). Categorical Data Analysis. Wiley, Hoboken, NJ. 2nd Edition.
## Not run: # Generate a random matrix containing 10 continuous variables # and a vector representing a continuous variable. mat <- matrix(runif(200, 0, 20), 10) y <- sample(runif(20, 0, 20)) # The correlations between y and each of row of mat are # computed by rowCors(mat, y) # Generate a random binary vector and a matrix consisting # of 10 ordinal variables with levels 0, 1, 2, where these # values can be interpreted as scores for the differ # categories. mat <- matrix(sample(0:2, 500, TRUE), 10) y <- sample(0:1, 50, TRUE) # The values of the Cochran-Armitage trend statistic are # computed by rowCors(mat, y, trendStat = TRUE) # If the values of the general test of linear trend described # on page 87 of Agresti (2002) should be computed, then call rowCors(mat, y, trendStat = TRUE, use.n = FALSE) ## End(Not run)
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