PROPHET StatGuide: Non-linear (Univariate) Regression
Non-linear univariate regression fits
a specified function in X to X-Y data by the method of least squares.
The full version of StatGuide for non-linear (univariate) regression will be available in a
future release. In the meantime, to properly analyze and interpret
results of non-linear (univariate) regression, you should be familiar with the following terms and
If you are not familiar with these terms and concepts, you are advised to
consult with a statistician. Failure to understand and properly apply
non-linear univariate regression may result in drawing erroneous conclusions from your data.
Additionally, you may want to consult the following references:
- Draper, N. R. and Smith, H. 1981.
Applied Regression Analysis. 2nd ed. New York: John Wiley & Sons.
- Neter, J., Wasserman, W., and Kutner, M.H. 1990. Applied
Linear Statistical Models. 3rd ed. Homewood, IL: Irwin.
- Scales, L. E. 1985. Introduction to Non-linear Optimization.
New York: Springer-Verlag.
- Sokal, Robert R. and Rohlf, F. James. 1995. Biometry. 3rd. ed.
New York: W. H. Freeman and Co.
Do a keyword search of PROPHET
Back to StatGuide modeling page.
Back to StatGuide home page.
Last modified: February 14, 1997
©1996 BBN Corporation All