• NLREG has been selected as the "Editor"s Pick" by SoftSeek.

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  • NLREG is in use at hundreds of universities, laboratories, and government agencies around the world (over 20 countries). For a list of a few organizations using NLREG click here.

  • If you have categorical variables, you may want to use a Decision Tree to model your data. Check out the DTREG Decision Tree Builder.

  • You also should check out the News Rover program that automatically scans Usenet newsgroups, downloads messages of interest to you, decodes binary file attachments, reconstructs files split across multiple messages, and eliminates spam and duplicate files.

    Linear Regression Example

    Linear regression fits a linear function of the form

    y = p0 + p1 * x

    to a set of data values. The values of the parameters p0 and p1 will be computed by NLREG so that the equation best fits the data values. Everything on a line after "//" is a comment.

    Title "Linear equation: y = p0 + p1*x";
    Variables x,y; // Two variables: x and y
    Parameters p0,p1; // Two parameters to be estimated: p0 and p1
    Function y = p0 + p1*x; // Model of the function
    Plot residual,grid; // Plot the function, data values and residuals
    [ data goes here ]

    In the plot, the blue "x" marks are the actual data points that were read in, the yellow line is the function that was fitted to the data, and the red vertical lines represent the residual values (i.e., the difference or error between the fitted data line and the actual data values).

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