Multilinear regression
Purpose
Description
Example
Macro Synopsis
Modules
Related Functions
References
Purpose
Multilinear regression
Description
"Multilinear regression" fits a linear combination of the components of a multi-channel signal x to a single-channel signal y and returns the residual (i.e. the difference signal)
of the multilinear regression
where 
are the channels of the multichannel
signal.
The computed coefficients 
and b are displayed in the message window.
Example
Use the macro LinComb.dpm to create a linear combination z
of two input signals x and y. Then generate a multichannel signal
s out of x and y using Merge.
Applying "Multilinear regression" to s and z will recover the coefficients
you used in the first step and yield a residual near 0 (the small
fluctuations are due to roundoff errors).
Macro Synopsis
r = MultiLinRegress([x,y]);
signal r,x,y;
Note that x is a multi-channel signal.
Modules
Statistics
Related Functions
Box-Cox transform, Detrended fluctuation analysis (DFA),
Exponential regression, Linear regression,
Power regression, Long term correlation analysis (LTCA),
Principal component analysis (PCA), R/S statistics,
Remove DC, Remove trend,
Split Merge.
References
Graybill [12]