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This is a shape preserving spline <doi:10.1137/0720057> which is guaranteed to be monotonic and concave or convex if the data is monotonic and concave or convex. It does not use any optimisation and is therefore quick and smoothly converges to a fixed point in economic dynamics problems including value function iteration. It also automatically gives the first two derivatives of the spline and options for determining behaviour when evaluated outside the interpolation domain.
| Version: | 1.2.1 |
| Suggests: | testthat, knitr, numDeriv, cobs, scam, rbenchmark |
| Published: | 2021-09-09 |
| Author: | Stuart Baumann [aut, cre], Margaryta Klymak[aut] |
| Maintainer: | Stuart Baumann <Stuart at StuartBaumann.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| In views: | NumericalMathematics |
| CRAN checks: | schumaker results |
| Reference manual: | schumaker.pdf |
| Vignettes: |
Schumaker Spline |
| Package source: | schumaker_1.2.1.tar.gz |
| Windows binaries: | r-devel: schumaker_1.2.1.zip, r-release: schumaker_1.2.1.zip, r-oldrel: schumaker_1.2.1.zip |
| macOS binaries: | r-release (arm64): schumaker_1.2.1.tgz, r-oldrel (arm64): schumaker_1.2.1.tgz, r-release (x86_64): schumaker_1.2.1.tgz, r-oldrel (x86_64): schumaker_1.2.1.tgz |
| Old sources: | schumaker archive |
| Reverse suggests: | FixedPoint |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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