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Cholesky #53
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Cholesky #53
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- LDL^T decomposition from Golub and Van Loan - UDU^T decomposition from Gibbs - Outer-product Cholesky decomposition from Golub and Van Loan - Rank-1 Cholesky update/downdate from Golub and Van Loan
| for i in 0:m -> | ||
| for j in 0:n -> | ||
| if i > j then b[i, j] <- 0.0 else b[i, j] <- a[i, j]; | ||
| ); |
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(sorry the built in upper triangular matrix type requires square dimensions). one alternative expression is:
vec i in 0:m -> vec j in 0:n -> if i > j then 0.0 else a[i,j];
then write
b <- triu a
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I just made this generic out of habit. All the decompositions in this module require symmetric (and therefore square) matrices. I'll try to use the built-in triangular matrix types.
I could also add the simple expression you wrote to the prelude.
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awesome! |
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Adds some useful decompositions for SPD matrices: