Scilab-Branch-6.1-GIT
Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
reglin
Linear regression
Syntax
[a,b,sig]=reglin(x,y)
Arguments
- x, y, a, b, sig
numerical vectors or matrices.
Description
Solve the regression problem y=a*x+b in the least square sense.
sig
is the standard deviation of the residual. x
and y
are two matrices of size x(p,n)
and y(q,n)
, where n
is the number of samples.
The estimator a
is a matrix of size (q,p)
and b
is a
vector of size (q,1)
.
If x
or y
contains NaNs, use nanreglin.
Examples
// Simulation of data for a(3, 5) and b(3, 1) x = rand(5, 100); aa = testmatrix("magi", 5); aa = aa(1:3, :); bb = [9; 10; 11]; y = aa*x +bb*ones(1, 100)+ 0.1*rand(3, 100); // Identification [a, b, sig] = reglin(x, y); max(abs(aa-a)) max(abs(bb-b)) // Another example: fitting a polynomial f = 1:100; x = [f.*f; f]; y = [2 3]*x + 10*ones(f) + 0.1*rand(f); [a, b] = reglin(x, y)
Graphical example:
See also
Report an issue | ||
<< princomp | Multivariate Correl Regress PCA | show_pca >> |