Slide 12 of 16
Notes:
Principal Component Regression
aka. Major axis regression, perpendicular distance method
Sum of the squared perpendicular distances of the m1 and m2 is minimised.
Limitations:
No bias between m1 and m2
Standard deviations of m1 and m2 are nearly identical
Range and domain are the same (i.e. m1 and m2 are of the same scale)
