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Classic calibration Standard regression assumes x values have no error Orthogonal distance regression (ODR) assumes both x and y have the same error variance.

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Presentation on theme: "Classic calibration Standard regression assumes x values have no error Orthogonal distance regression (ODR) assumes both x and y have the same error variance."— Presentation transcript:

1 Classic calibration Standard regression assumes x values have no error Orthogonal distance regression (ODR) assumes both x and y have the same error variance

2 Calibrating buoys and satellites (and errors) at the same time Peter Challenor SOC

3 New method Assume that the true values are fixed but unknown Estimate the x’s as well as the regression parameters Indeterminacy so fix one regression to slope 1 and intercept 0

4 Mathematically Standard regression: all error on y Orthogonal Distance Regression : error equal on x and y New method. Estimate true value x

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6 Results NDBCJASONTOPEXUKCMENVISAT Intercept (m) (0.014) (0.007) (0.029) (0.007) Slope (0.005) (0.002) (0.011) (0.002) Residual std dev (m)

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