Hello,

If you have a numeric matrix or data.frame, try something like

cov(mtcars)

Hope this helps,

Rui Barradas


Às 10:15 de 04/10/2024, Steven Yen escreveu:
On 10/4/2024 5:13 PM, Steven Yen wrote:

Pardon me!!!

What makes you think this is a homework question? You are not
obligated to respond if the question is not intelligent enough for you.

I did the following: two ways to calculate a covariance matrix but
wonder how I might replicate the results with "apply". I am not too
comfortable with the online documentation of "apply".

set.seed(122345671) > n<-3 > x<-rnorm(n); x [1] 0.92098449 0.80940115
0.60374785 > cov1<-outer(x-mean(x),x-mean(x))/(n-1); cov1 [,1] [,2]
[,3] [1,] 0.0102159207 0.00224105983 -0.0124569805 [2,] 0.0022410598
0.00049161983 -0.0027326797 [3,] -0.0124569805 -0.00273267965
0.0151896601 > cov2<-(x-mean(x))%*%t((x-mean(x)))/(n-1); cov2 [,1]
[,2] [,3] [1,] 0.0102159207 0.00224105983 -0.0124569805 [2,]
0.0022410598 0.00049161983 -0.0027326797 [3,] -0.0124569805
-0.00273267965 0.0151896601 >
On 10/4/2024 4:57 PM, Uwe Ligges wrote:
Homework questions are not answered on this list.

Best,
Uwe Ligges



On 04.10.2024 10:32, Steven Yen wrote:
The following line calculates standard deviations of a column vector:

se<-apply(dd,1,sd)

How can I calculate the covariance matrix using apply? Thanks.

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