I am trying to find linear decomposition of vector B (of arbitrary dimension $n$) in the form :
$B = \alpha_{1} C_{1} + \alpha_{2} C_{2} + ...$
where $C_{i}$ are known vectors (of dimension $n$) and $\alpha_{i}$ are scalars (to be determined).
I am trying to do it using LinearFitModel
, but I have trouble understanding how it works in my case from the Mathematica documentation. I tried :
X = Transpose[{C1,C2,C3,X}]
f = Transpose[{C1,C2,C3}]
t = Table[i,{i,1,Length[X]}]
LinearModelFit[X,f,t]
but I get the following error :
LinearModelFit::fitm: Unable to solve for the fit parameters; the design matrix is nonrectangular, non-numerical, or could not be inverted.
Has someone experience with this ?
Many thanks in advance,
Cl38
LinearSolve[]
looks to be better for this. $\endgroup$