| Calling Sequence
| LinearRegerssion(y,x1,...)
|
| Parameters
| | Name | Type | Description |
|
| y
| array(numeric) | dependent variable |
| x1
| array(numeric) | independent variable(s) |
|
| Return Type
| array(numeric) |
| Globals
| SumSq, |
| Synopsis
| Computes a linear regression y = a0 + a1*x1 + a2*x2 + ...
by least squares. The number of arguments is variable,
it should be at least 2. LinearRegression returns the vector
[a0,a1,a2,...]. The global variable SumSq is set to the
sum of squares of errors in the regression. |
| Examples
| > LinearRegression( [2.1,3.01,3.9,4.89], [0,1,2,3] );
[2.0860, 0.9260]
> SumSq;
0.00232000
|
| See also
| ExpFit, ExpFit2, Stat, SvdAnalysis |