Least squares

Related lectures (29)

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Explains least squares approximation for finding best fit lines or curves to data points.

Explores linear regression estimation, hypothesis testing, and practical applications in statistics.

Explores standardizing variables and effects in multilinear regression analysis.

Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.

Covers the identification and model specification in time series analysis, including AR models and least squares estimation.

Introduces the Gram-Schmidt algorithm, QR factorization, and the method of least squares.

Explores least squares in linear regression, hypothesis testing, outliers, and model assumptions.

Explains how to solve linear equations using the least squares method to minimize errors in the system.

Covers the basics of multilinear regression and its application in analyzing material properties.

Covers the Recursive Least-Squares algorithm with weighted formulation for real-time data updating.