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legendrefit

# legendrefit - function varargout = legendrefit(Y N...

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Unformatted text preview: function varargout = legendrefit(Y, N, method) %LEGENDREFIT Fitting data using a linear combination of Legendre polynomials % % A = legendrefit(Y, N, method) finds the column vector A which contains % weighting coefficients of the linear combination of a set of Legendre % polynomials up to order N. A(i) is the weight of P_{i-1}(x) which is % Legendre polynomial of order i-1. The fitting is optimum in the least % squares sense. If N is not specified, default order 2 is used. % % Three methods are available (just for fun): 'inv' (default) inverts the % normal equation matrix directly, while 'chol' and 'qr' find the solution % via Cholesky and QR decomposition, respectively. % % [A Y2] = legendrefit(...) returns the fitting (regression) result Y2, % i.e. Y2 = \sum_{i=1}^{N+1} A(i)*P_{i-1}(x). Residuals are then Y - Y2. % % [A Y2 r] = legendrefit(...) and [A Y2 r e] = legendrefit(...) further % return the Pearson's correlation coefficient r and root mean square % error (RMSE) e, respectively....
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legendrefit - function varargout = legendrefit(Y N...

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