![]() In Appendix I, procedures and methods to formulate empirical equations are discussed. ![]() Both ALESQ and TSOLVE can also be used for linear problems. ![]() ![]() A routine to estimate tolerances for roundoff of the solution has been developed and included in TSOLVE. The code for this algorithm is called TSOLVE. The algorithm used for the best approximation is basically the one developed by Osborne and Watson a method to obtain the solution for the continuous best-approximation problem with a discrete set of data has been incorporated. For fitting the equation to the data with approximately equal relative uncertainties, a two-step method is proposed, and conveniences for this method are provided in ALESQ. ![]() The code for this algorithm is called ALESQ. The algorithm used for the least-squares fit is based on the maximum neighborhood algorithm developed by Levenberg and Marquardt an improvement in strategy proposed by the present authors has been incorporated. ![]()
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