Overview

Curve Fitting Toolbox provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives. The most important content is the following: -Nonparametric Fitting -Interpolation Methods -Selecting an Interpolant Fit -Smoothing Splines -Lowess Smoothing -Fit Smooth Surfaces To Investigate Fuel Efficiency -Filtering and Smoothing Data -Introducing Spline Fitting -Curve Fitting Toolbox Splines and MATLAB Splines -Cubic Spline Interpolation -Vector-Valued Functions -Fitting Values at N-D Grid with Tensor-Product -Splines -Fitting Values at Scattered 2-D Sites with Thin-Plate -Smoothing Splines -Postprocessing Splines -Types of Splines: ppform and B-form -B-Splines and Smoothing Splines -Multivariate and Rational Splines -The ppform -Constructing and Working with ppform Splines -The B-form -B-form and B-Splines -B-Spline Knot Multiplicity -Choice of Knots for B-form -Constructing and Working with B-form Splines -Multivariate Tensor Product Splines -B-form of Tensor Product Splines -Construction With Gridded Data -ppform of Tensor Product Splines -NURBS and Other Rational Splines -Constructing and Working with Rational Splines -Constructing and Working with stform Splines -Least-Squares Approximation by Natural Cubic Splines -Solving A Nonlinear ODE -Construction of the Chebyshev Spline -Approximation by Tensor Product Splines

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9781979562706

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