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(NOTE: This answer explains why R and RcppArmadillo return matrices with different dimensions, but not how to make RcppArmadillo return the 1000*20 matrix that R does. For that, perhaps take a look at the strategy used near the bottom of the <code>qr.Q()</code> function definition.) <hr> R's <code>qr()</code> function does not return Q directly. For that, you need to use <code>qr.Q()</code>, like this: <pre><code>m <- matrix(rnorm(10), ncol=2) qr.Q(qr(m)) # [,1] [,2] # [1,] -0.40909444 0.05243591 # [2,] 0.08334031 -0.07158896 # [3,] 0.38411959 -0.83459079 # [4,] -0.69953918 -0.53945738 # [5,] -0.43450340 0.06759767 </code></pre> Notice that <code>qr.Q()</code> returns a matrix of the the same dimension as <code>m</code>, rather than a full 5*5 Q matrix. You can use the <code>complete=</code> argument to control this behavior, and get a Q matrix of full dimension: <pre><code>qr.Q(qr(m), complete=TRUE) # [,1] [,2] [,3] [,4] [,5] # [1,] -0.40909444 0.05243591 0.3603937 -0.7158951 -0.43301590 # [2,] 0.08334031 -0.07158896 -0.8416121 -0.5231477 0.07703927 # [3,] 0.38411959 -0.83459079 0.2720003 -0.2389826 0.15752300 # [4,] -0.69953918 -0.53945738 -0.2552198 0.3453161 -0.18775072 # [5,] -0.43450340 0.06759767 0.1506125 -0.1935326 0.86400136 </code></pre> In your case, it sounds like RcppArmadillo is returning the full 1000x1000 Q matrix (like <code>qr.Q(q(m, complete=FALSE))</code> would), rather than just its 1st 20 columns (like <code>qr.Q(q(m))</code> would).
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