Curve Fitting and Smoothing Functions

Linear Regression

line, medfit, slope, and intercept Least-squares linear regression and median-median line regression for data.

stderr Returns the standard error associated with linear regression.

Generalized Regression

genfit Least-squares nonlinear regression for arbitrary fit functions.

linfit Least-squares regression for an arbitrary linear combination of functions.

Polynomial Regression, univariate and multivariate

regress and interp Find the polynomial least-squares fit to a set of data points.

loess and interp Find the set of second order polynomials that best fit particular neighborhoods of data points.

Specialized Regression

These functions save steps for commonly used nonlinear regression functions and don't require definition of derivatives with respect to the parameters. They sometimes also supply their own guess values.

expfit Least-squares exponential regression.

lnfit and logfit Least-squares logarithmic regression.

lgsfit Least-squares logistic curve regression.

pwrfit Least-squares power curve regression.

sinfit Least-squares sinusoidal regression.

Smoothing Data