# Orthogonal linear regression in matlab

The following Matlab project contains the source code and Matlab examples used for orthogonal linear regression. LINORTFIT2(X,Y) finds the coefficients of a 1st-order polynomial that best fits the data (X,Y) in an ORTHOGONAL least-squares sense.

# Non parametric regression using kernels to estimate density function of residuals. in matlab

The following Matlab project contains the source code and Matlab examples used for non parametric regression using kernels to estimate density function of residuals. . It will first to a simple regression using least squares to get a good start value.

# Solution of one or more nonlinear equations in the least squares sense. in matlab

The following Matlab project contains the source code and Matlab examples used for solution of one or more nonlinear equations in the least squares sense. . The function is an improved version of the function LMFnlsq widely tested on the nonlinear regression, curve fitting and identification problems.

# Plane fitting and normal calculation in matlab

The following Matlab project contains the source code and Matlab examples used for plane fitting and normal calculation. Given a set of x,y,z coordinates, find the best planar fit to the points via a least squares regression.

# Efficient nonlinear regression fitting using a constrained, partitioned least squares overlay to fmi in matlab

The following Matlab project contains the source code and Matlab examples used for efficient nonlinear regression fitting using a constrained, partitioned least squares overlay to fmi . I need to thank Duane Hanselman for suggesting this great idea. 