Question

I was wondering what is your recommended way to compute the inverse of a matrix?

The ways I found seem not satisfactory. For example,

> c=rbind(c(1, -1/4), c(-1/4, 1))  
> c  
      [,1]  [,2]  
[1,]  1.00 -0.25  
[2,] -0.25  1.00  
> inv(c)  
Error: could not find function "inv"  
> solve(c)    
          [,1]      [,2]  
[1,] 1.0666667 0.2666667  
[2,] 0.2666667 1.0666667  
> solve(c)*c  
            [,1]        [,2]  
[1,]  1.06666667 -0.06666667  
[2,] -0.06666667  1.06666667  
> qr.solve(c)*c  
            [,1]        [,2]  
[1,]  1.06666667 -0.06666667  
[2,] -0.06666667  1.06666667  

Thanks!

Était-ce utile?

La solution

solve(c) does give the correct inverse. The issue with your code is that you are using the wrong operator for matrix multiplication. You should use solve(c) %*% c to invoke matrix multiplication in R.

R performs element by element multiplication when you invoke solve(c) * c.

Autres conseils

You can use the function ginv() (Moore-Penrose generalized inverse) in the MASS package

Note that if you care about speed and do not need to worry about singularities, solve() should be preferred to ginv() because it is much faster, as you can check:

require(MASS)
mat <- matrix(rnorm(1e6),nrow=1e3,ncol=1e3)

t0 <- proc.time()
inv0 <- ginv(mat)
proc.time() - t0 

t1 <- proc.time()
inv1 <- solve(mat)
proc.time() - t1 
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