Note that fitting polynomial coefficients is inherently badly conditioned Values can add numerical noise to the result. The rcond parameterĬan also be set to a value smaller than its default, but the resultingįit may be spurious: including contributions from the small singular The results may be improved by lowering the polynomialĭegree or by replacing x by x - x.mean(). This implies that the best fit is not well-defined due Polyfit issues a RankWarning when the least-squares fit is badlyĬonditioned. The coefficient matrix of the coefficients p is a Vandermonde matrix. The warning is only raised if full = False. The rank of the coefficient matrix in the least-squares fit isĭeficient. Is a 2-D array, then the covariance matrix for the k-th data set This matrix are the variance estimates for each coefficient. Matrix of the polynomial coefficient estimates. Present only if full = False and cov = True.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |