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Simplified forecasting by polynomial regression with equally spaced values of the independent variable


Authors: Jack Laderman and Julian D. Laderman
Journal: Math. Comp. 38 (1982), 601-610
MSC: Primary 62J02; Secondary 65U05
DOI: https://doi.org/10.1090/S0025-5718-82-99830-1
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Abstract | References | Similar Articles | Additional Information

Abstract: A method is developed and tables are presented which yield polynomial least squares forecasts by computing the inner product of two n-component vectors, where n is the number of observed points.


References [Enhancements On Off] (What's this?)

  • [1] A. Fletcher, J. C. P. Miller, L. Rosenhead & L. J. Comrie, An Index of Mathematical Tables, Vol. 1, 2nd ed., Addison-Wesley, Reading, Mass., 1962, pp. 594-596. MR 0142796 (26:365a)
  • [2] Jack Laderman, "The square root method for solving simultaneous linear equations," MTAC, v. 3, 1948, pp. 13-16. MR 0025263 (9:622b)
  • [3] James Singer, Elements of Numerical Analysis, Academic Press, New York, 1964, p. 99. MR 0165652 (29:2932)

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Additional Information

DOI: https://doi.org/10.1090/S0025-5718-82-99830-1
Keywords: Forecasting by least squares, finite differences, matrix inversion by the square root method
Article copyright: © Copyright 1982 American Mathematical Society

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