Multiple regression: Difference between revisions

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You can assume <i>y</i> is given to you as an array, and <i>x</i> is given to you as a two-dimensional array.
 
Note: This is more general than [[Polynomial Fitting]], which only deals with 2 datasets and only deals with polynomial equations. Ordinary least squares can deal with an arbitrary number of datasets (limited by the processing power of the machine) and can have more advanced equations such as:
<math>y = \beta_1log(x_1) + \beta_22^{x_1} + \beta_3sin(x_2)</math>
 
=={{header|Haskell}}==
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