I'm trying to do a linear regression between the columns of matrices. In
example below I want to regress column 1 of matrix xdat with column1 of ydat
and do a separate regression between the column 2s of each matrix. But the
output I get seems to give correct slopes but incorrect intercepts and
another set of slopes with value NA. How do I do this correctly? I'm after
the slope and intercept of each columns regression
> xdat <- matrix(1:6,3,2)
> xdat
[,1] [,2]
[1,] 1 4
[2,] 2 5
[3,] 3 6
> ydat <- xdat
> ydat[,1] <- xdat[,1]*3 +2
> ydat
[,1] [,2]
[1,] 5 4
[2,] 8 5
[3,] 11 6
> ydat[,2] <- xdat[,2]*4 - 3
> yadt
Error: object "yadt" not found
> ydat
[,1] [,2]
[1,] 5 13
[2,] 8 17
[3,] 11 21
> lrg <- lm(y~x)
Error in eval(expr, envir, enclos) : object "y" not found
> lrg <- lm(ydat~xdat)
> lrg
Call:
lm(formula = ydat ~ xdat)
Coefficients:
[,1] [,2]
(Intercept) 2 9
xdat1 3 4
xdat2 NA NA
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