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Based on the singular value decomposition, a singular equation system ax=b is solved.
gsi.svdsolve(a,b,...,cond=1E-10)
The "smallest" vector or matrix solving this system with minimal joint error among all vectors.
the matrix of ax=b (a.k.a. left-hand side matrix)
the vector or matrix b of ax=b (a.k.a right-hand side, independent element)
the smallest-acceptable condition of the matrix. Smaller singular values are truncate
additional arguments to svd
K.Gerald v.d. Boogaart http://www.stat.boogaart.de
#A <- matrix(c(0,1,0,0,0,0),ncol=2) #b <- diag(3) #erg <- gsi.svdsolve(A,b) #erg #A %*% erg #diag(c(0,1,0)) # richtig
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