one way is the following:
A <- replicate(10, cor(matrix(rnorm(30), 10, 3)), simplify = FALSE)
triA <- sapply(A, function (m) m[upper.tri(m)])
rowMeans(triA, na.rm = TRUE)
I hope it helps.
Best,
Dimitris
On 11/9/2010 9:23 AM, Suphajak Ngamlak wrote:
Dear all,
I have a list of correlation coefficient matrixes. Each matrix represents one
date.
For example
A[[1]]
A B C
A 1 0.2 0.3
B 0.2 1 0.4
C 0.3 0.4 1
A[[2]]
A B C
A 1 0.5 0.6
B 0.5 1 0.7
C 0.6 0.7 1
....
A[[n]]
I would like to calculate the mean of correlation coefficient from the whole
time series, i.e.
Average cor(A,B) = (A[[1]][2,1] + A[[2]] [2,1] + ... + A[[n]] [2,1])/n
Average cor(A,C) = (A[[1]][3,1] + A[[2]] [3,1] + ... + A[[n]] [3,1])/n
Average cor(B,C) = (A[[1]][3,2] + A[[2]] [3,2] + ... + A[[n]] [3,2])/n
Please note that some cells are NA; so I need to remove them when calculating
average.
How could I get this efficiently? Thank you
Best Regards,
Suphajak Ngamlak
Equity and Derivatives Trading
Phatra Securities Public Company Limited
Tel: (66)2-305-9179
Email: supha...@phatrasecurities.com
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--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
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