In addition, the algorithm is made adaptive to local data structure by estimating the parameter of an unknown original signal.C.S. KimC.N. Shen **Systems Approaches in Computer Science and MathematicsC. S. Kim and C. N. Shen, "A Recursive Algorithm for Smoothing by Spline Functions," Proceedings of the International ...
[1] C. Reinsch. "Smoothing by spline functions."Numer. Math. 10 (1967), 177–183. Version History Introduced before R2006a Select a Web Site Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select...
Optimal smoothing parameter selection for... Learn more about csaps, smoothing spline, curve fitting, spaps, cubic spline, spline interpolation
首页 翻译 背单词 英文校对 词霸下载 用户反馈 专栏平台 登录 翻译 Smoothingsplinefunctions 翻译 平滑样条函数 以上结果来自机器翻译。 释义
For an alternative to'smoothingspline', you can use thecsapscubic smoothing spline function or other spline functions that allow greater control over what you can create. SeeIntroducing Spline Fitting. Compare Cubic and Smoothing Spline Fit Using Curve Fitter ...
C. H. Reinsch, Smoothing by Spline Functions. II, Numer. Math., 16 (1971), pp. 451–454. CrossRef A. Savitzky AND M. J. E. Golay, Smoothing and Differentiation of Data by Simplified Least Squares Procedures, Analytical Chemistry, 36 (1964), pp. 1627–1639. CrossRef J. Steinier...
C.H. Reinsch Smoothing by spline functions Numer. Math., 10 (1967), pp. 177-183 View in ScopusGoogle Scholar 14 L.L. Schumaker Fitting surfaces to scattered data G.G. Lorentz, C.K. Chui, L.L. Schumaker (Eds.), Approximation Theory II, Academic (1976), pp. 203-267 Google Scholar...
Several methods have been proposed to test the hypothesis of a parametric regression function against an alternative smoothing spline model. Some tests such as the locally most powerful (LMP) test by Cox et al. (Cox, D., Koh, E., Wahba, G. and Yandell, B. (1988). Testing the (...
Secondly, its global smoothing parameter can only provide constant amount of smoothing, which often results in poor performances when estimating inhomogeneous functions. In this work, we introduce a class of adaptive smoothing spline models that is derived by solving certain stochastic differential ...
The smoothing spline f minimizes the roughness measure F(D^2 f) := integral ( D^2 f(t) )^2 dt on X(1) < t < X(n) over all functions f for which the error measure E(f) := sum_j { W(j)*( Y(:,j) - f(X(j)) )^2 : j=1,...,n } ...