hadamard {survey} | R Documentation |
Returns a Hadamard matrix of dimension larger than the argument.
hadamard(n)
n |
lower bound for size |
For most n
the matrix comes from paley
. The
36x36 matrix is from Plackett and Burman (1946)
and the 28x28 is from Sloane's library of Hadamard
matrices.
Matrices of dimension every multiple of 4 are thought to exist, but this function doesn't know about all of them, so it will sometimes return matrices that are larger than necessary. The excess is at most 4 for n<180 and at most 5% for n>100.
A Hadamard matrix
Strictly speaking, a Hadamard matrix has entries +1 and -1 rather
than 1 and 0, so 2*hadamard(n)-1
is a Hadamard matrix
Sloane NJA. A Library of Hadamard Matrices http://www.research.att.com/~njas/hadamard/
Plackett RL, Burman JP. (1946) The Design of Optimum Multifactorial Experiments Biometrika, Vol. 33, No. 4 pp. 305-325
Cameron PJ (2005) Hadamard Matrices http://designtheory.org/library/encyc/topics/had.pdf. In: The Encyclopedia of Design Theory http://designtheory.org/library/encyc/
par(mfrow=c(2,2)) ## Sylvester-type image(hadamard(63),main=quote("Sylvester: "*64==2^6)) ## Paley-type image(hadamard(59),main=quote("Paley: "*60==59+1)) ## from NJ Sloane's library image(hadamard(27),main=quote("Stored: "*28)) ## For n=90 we get 96 rather than the minimum possible size, 92. image(hadamard(90),main=quote("Constructed: "*96==2^3%*%(11+1))) par(mfrow=c(1,1)) plot(2:150,sapply(2:150,function(i) ncol(hadamard(i))),type="S", ylab="Matrix size",xlab="n",xlim=c(1,150),ylim=c(1,150)) abline(0,1,lty=3) lines(2:150, 2:150-(2:150 %% 4)+4,col="purple",type="S",lty=2) legend(c(x=10,y=140),legend=c("Actual size","Minimum possible size"), col=c("black","purple"),bty="n",lty=c(1,2))