Fit curve or surface to data - MATLAB fit

$ 17.50 · 4.9 (723) · In stock

This MATLAB function creates the fit to the data in x and y with the model specified by fitType.
Load the census sample data set.
Load the franke sample data set.
Load the franke data and convert it to a MATLAB® table.
Load and plot the data, create fit options and fit type using the fittype and fitoptions functions, then create and plot the fit.
Load the carbon12alpha nuclear reaction sample data set.
Load the census sample data set. Fit a cubic polynomial and specify the Normalize (center and scale) and Robust fitting options.
Load some data and fit a custom equation specifying points to exclude. Plot the results.
You can define the excluded points as variables before supplying them as inputs to the fit function. The following steps recreate the fits in the previous example and allow you to plot the excluded points as well as the data and the fit.
Generate some noisy data using the membrane and randn functions.
Fit a smoothing spline curve, and return goodness-of-fit statistics and information about the fitting algorithm.
Generate data with an exponential trend, and then fit the data using the first equation in the curve fitting library of exponential models (a single-term exponential). Plot the results.
For the properties Upper, Lower, and StartPoint, you need to find the order of the entries for coefficients.