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https://statistics.stanford.edu/sites/default/.../OLK%20NSF%20216.pdfGENERATION OF RANDOM ORTHOGONAL MATRICES by. T. W. Anderson, I.
Olkin, L.G. Underhill. Technical Report No. 216. August 1985. Prepared under
the Auspices of. National Science Foundation. DMS 84-11411. Ingram Olkin,
Project Director. Department of Statistics. Stanford University. Stanford, California
epubs.siam.org/doi/abs/10.1137/0908055T. W. Anderson, I. Olkin, and L. G. Underhill · https://doi.org/10.1137/0908055. In
order to generate a random orthogonal matrix distributed according to Haar
measure over the orthogonal group it is natural to start with a matrix of normal
random variables and then factor it by the singular value decomposition. A more
dl.acm.org/citation.cfm?id=36016Jul 1, 1987 ... Generation of random orthogonal matrices. Authors: T. W. Anderson · Stanford
Univ., Stanford, ... AUTHORS. Author image not provided, T. W. Anderson. No
contact information provided yet. Bibliometrics: publication history ... Average
citations per article, 4.00. View colleagues of L. G. Underhill. top of page ...
citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.33...With this method, an. n n matrix X is rst generated with entries xij. N ormal(0;1).
Then a QR factorization (X = QR) is computed. This method provides a random Q
with correct distribution. Stewart (1980) and Anderson, Olkin and Underhill (1987
) re ned the basic Heiberger algorithm by developing methods that construct Q.
www.math.wsu.edu/faculty/genz/papers/rndorth.psWith this method, an. n n matrix X is rst generated with entries x. ij. Normal(0;1).
Then a QR. factorization (X = QR) is computed. This method provides a random Q
with. correct distribution. Stewart (1980) and Anderson, Olkin and Underhill (1987
). re ned the basic Heiberger algorithm by developing methods that construct Q.
https://www.researchgate.net/...random_orthogonal_matrices/.../ 0deec51a869c188c8e000000.pdfMay 22, 2013 ... Tensor product of random orthogonal matrices. M Arioli. May 2013. Technical
Report. RAL-TR-2013-006 ... Key words. Random orthogonal matrices, sparse
matrices, Gaussian factorization, pivoting. AMS subject .....  T. W. Anderson, I.
Olkin, and L. G. Underhill, Generation of random orthogonal matrices,.
André I. Khuri - 2003 - Mathematics
Another example is the generation of random orthogonal matrices for carrying out
simulation experiments. This was used by Heiberger, Velleman, and Ypelaar
Ž1983. to construct test data with special properties for multivariate linear models.
Anderson, Olkin, and Underhill Ž1987. proposed a procedure to generate
Charles R. Johnson, American Mathematical Society - 1990 - Mathematics
Anderson, T.W. and Olkin, I. (1985). Maximum-likelihood estimation of the
parameters of a multivariate normal distribution. Linear Algebra and Its
Applications, 70, 147–171. Anderson, T.W., Olkin, I., and Underhill, L. (1987).
Generation of random orthogonal matrices. SIAM Journal of Scientific and
Statistical Computing, ...