LINEAR ALGEBRA

linear least squares

Find the coefficient that minimizes the sum of the squared errors of the predicted value and the observed value.

β^=(XTX)−1XTy\hat\beta=(X^{T}X)^{-1}X^{T}y

symbols, variables and units

X: design matrix; y: observation vector; β: regression coefficient, units are defined in columns.

applicable conditions and boundaries

X must have full column rank; use QR or SVD in numerical calculations rather than explicitly inverting the matrix.

formula source code

The following is a copyable LaTeX expression.

\hat\beta=(X^{T}X)^{-1}X^{T}y

Reference and Extended Learning

MIT OpenCourseWare · Linear Algebra ↗

is organized according to model definition and assumptions. Please check actual conditions and original literature before engineering, research and clinical use.

least squaresreturns

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