How to use weights in multivariate linear regression in R with lm?

Asked Nov 20 '19 at 22:35

Active Nov 20 '19 at 23:11

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I've got a linear regression that looks like:

multivariateModel = lm(cbind(y1, y2, y3)~., data=temperature)

I need to do two things with this, which I've found difficult to do. First is to extract the variances, and right now I'm using sigma(multivariateModel), which has returned

  y1       y2       y3

31.22918 31.83245 31.01727

I would like to use those 3 sigmas to create variances (sd^2) and weight them against my regression. Currently, weights=cbind(31.22918, 31.83245, 31.01727) is not working, and it's also not working to use matrix 3 columns long with those values repeated.

Here is the dataset in question:

Is there a way to add these as a weighted matrix so that I can get out a fitted model with this, or is there another package I need to use besides lm for this? Thanks.

Here is a link to the dataset: https://docs.google.com/spreadsheets/d/1zm9pPqOnkBdsPekOf8IoXN8yLr82CCFBuc9EtxN5JII/edit?usp=sharing

edited Nov 20 '19 at 23:11

asked Nov 20 '19 at 22:35

That One Dude Mike

Can you edit your question to include a [reproducible example](https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example) of your dataset ? – dc37 Nov 20 '19 at 22:55
It has been added. – That One Dude Mike Nov 20 '19 at 23:03
Please read carefully the link that I provide you. Right now, your dataset presented as an image is not suitable for copy/paste. – dc37 Nov 20 '19 at 23:06
I added a link to the dataset. – That One Dude Mike Nov 20 '19 at 23:13

How to use weights in multivariate linear regression in R with lm?

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