Abstract
In [3] Boneva, Kendall and Stefanov (B.K.S.) have effectively rediscovered the essential features of what I like to call cardinal cubic spline interpolation. Moreover, and this is an important point, the data are not the usual function values that are to be interpolated, but rather approximations of the derivative (i.e. the unknown density function) in the form of a histogram. This (pershaps only apparent) difference is bridged by the ingenious area-matching condition.
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Schoenberg, I.J. (1973). Splines and Histograms. In: Meir, A., Sharma, A. (eds) Spline Functions and Approximation Theory. ISNM International Series of Numerical Mathematics / Internationale Schriftenreihe zur Numerischen Mathematik / Série Internationale d’Analyse Numérique, vol 21. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-5979-0_13
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