Linear least-squares projection

The best affine predictor has slope covariance divided by predictor variance and intercept chosen to match means.

Table of contents
- Schur complement covariance Linear least-squares projection

Schur complement covariance

The residual variance after projection onto one factor is

Var (Y) - Cov (X, Y)^{2} / Var (X)

, a covariance Schur complement.

 Ancestors (4)

 Incoming links (6)

Bühlmann credibility premium
Least-squares projection of filament deformation velocity
Past exam of the mathematics course of the University of Cambridge / 2003 / iii / Paper 43 / 5 / Solution
Past exam of the mathematics course of the University of Cambridge / 2013 / iii / Paper 28 / 4 / a / Solution
Past exam of the mathematics course of the University of Cambridge / 2014 / iii / Paper 31 / 4 / Solution
Past exam of the mathematics course of the University of Cambridge / 2015 / iii / Paper 34 / 4 / Solution

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