Re: [R] getting covariance ignoring NaN missing values

.21850006 0.4433438 > A.K. > > > > > - Original Message - > From: Sachinthaka Abeywardana > To: "r-help@r-project.org" > Cc: > Sent: Thursday, March 7, 2013 10:36 PM > Subject: [R] getting covariance ignoring NaN missing values > > Hi al

Re: [R] getting covariance ignoring NaN missing values

,2]   [,3] #[1,]  1.2570603 -0.32167789  0.7377472 #[2,] -0.3216779  0.08371491 -0.2185001 #[3,]  0.7377472 -0.21850006  0.4433438 A.K. - Original Message - From: Sachinthaka Abeywardana To: "r-help@r-project.org" Cc: Sent: Thursday, March 7, 2013 10:36 PM Subject: [R] g

[R] getting covariance ignoring NaN missing values

Hi all, I have a matrix that has many NaN values. As soon as one of the columns has a missing (NaN) value the covariance estimation gets thrown off. Is there a robust way to do this? Thanks, Sachin a=array(rnorm(9),dim=c(3,3))> a[,1] [,2] [,3] [1,] -0.79418236 0.7813952