ABSTRACT
The primary purpose of TSPACK is to construct a smooth function which interpolates a discrete set of data points. The function may be required to have either one or two continuous derivatives. If the accuracy of the data does not warrant interpolation, a smoothing function (which does not pass through the data points) may be constructed instead. The fitting method is designed to avoid extraneous inflection points (associated with rapidly varying data values) and preserve local shape properties of the data (monotonicity and convexity), or to satisfy the more general constraints of bounds on function values or first derivatives. The package also provides a parametric representation for construction general planar curves and space curves.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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DE BOOR, C. A Practical Guide to Spltnes. Springer-Verlag, New York, 1978.
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FRITSCH, F. N., AND BUTLAND, J. A method for constructing local monotone p~ecewise cubic interpolants. SIAM J. Sct. Stat. Comput. 5, 2 (June 1984), 300 304.
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FRITSCH, F. N., AND CARLSON, R. E. Monotone piecewise cubic interpolation. SIAM J. Numer. Anal 17, 2 (Apr. 1988), 238-246.
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RE~NSC}t, C.H. Smoothing by spline functions. Numer. Math. lO (1967), 177-183.
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REINSCH, C.H. Smoothing by spline functions II. Numer. Math. 16 (1971), 451-454.
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INDEX TERMS
Primary Classification:
G.
Mathematics of Computing
Additional Classification:
G.
Mathematics of Computing
G.1
NUMERICAL ANALYSIS
General Terms:
Algorithms
Keywords:
convexity preserving,
cubic spline,
exponential spline,
interpolation,
monotonicity preserving,
parametric curve,
piecewise polynomial,
shape preserving,
smoothing,
spline under tension,
tension factor
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