QR factorization simplifies solving linear systems by decomposing a matrix into an orthogonal Q and upper-triangular R. This chapter shows how Rx⃗ = Qᵀb⃗ provides a numerically stable alternative to the normal equations for ordinary least squares (OLS) and data fitting.
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