Mod 5 matrices

Daniel Tafmizi

Dr. Friedman

Lis 4370

Module 5

Github: daniel.R/Work.R/LIS4370Rprog/Mod5.R at main · DanielDataGit/daniel.R (github.com)


The provided matrices were singular and non-square. For linear systems, finding an inverse of these types requires a variation of Singular Value Decomposition (SVD), which essentially breaks down a matrix into three parts (the rows, the columns, and its diagonal "time/instance order"). R's matlib library provides the function ginv(), which uses the Moore-Penrose inverse to create a generalized inverse that is useful in solving linear systems. The formula is A+=VD+UT, where V is an orthogonal row matrix, D+ is the transposed reciprocal of all non-zero values in the diagonal matrix, and UT is the transposed orthogonal column matrix. It is used to calculate an approximate solution to an "unsolvable" linear system. 

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