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cran

interp:Interpolation Methods

Bivariate data interpolation on regular and irregular grids, either linear or using splines are the main part of this package. It is intended to provide FOSS replacement functions for the ACM licensed akima::interp and tripack::tri.mesh functions. Linear interpolation is implemented in interp::interp(..., method="linear"), this corresponds to the call akima::interp(..., linear=TRUE) which is the default setting and covers most of akima::interp use cases in depending packages. A re-implementation of Akimas irregular grid spline interpolation (akima::interp(..., linear=FALSE)) is now also available via interp::interp(..., method="akima"). Estimators for partial derivatives are now also available in interp::locpoly(), these are a prerequisite for the spline interpolation. The basic part is a GPLed triangulation algorithm (sweep hull algorithm by David Sinclair) providing the starting point for the irregular grid interpolator. As side effect this algorithm is also used to provide replacements for almost all functions of the tripack package which also suffers from the same ACM license restrictions. All functions are designed to be backward compatible with their akima / tripack counterparts.

Maintained by Albrecht Gebhardt. Last updated 1 years ago.

fortrancpp

1 stars 7.76 score 287 dependents

goepp

aspline:Spline Regression with Adaptive Knot Selection

Perform one-dimensional spline regression with automatic knot selection. This package uses a penalized approach to select the most relevant knots. B-splines of any degree can be fitted. More details in 'Goepp et al. (2018)', "Spline Regression with Automatic Knot Selection", <arXiv:1808.01770>.

Maintained by Vivien Goepp. Last updated 3 years ago.

adaptive-splinesfitting-splinesknotsregression-splinecpp

6 stars 4.52 score 11 scripts

cran

akima:Interpolation of Irregularly and Regularly Spaced Data

Several cubic spline interpolation methods of H. Akima for irregular and regular gridded data are available through this package, both for the bivariate case (irregular data: ACM 761, regular data: ACM 760) and univariate case (ACM 433 and ACM 697). Linear interpolation of irregular gridded data is also covered by reusing D. J. Renkas triangulation code which is part of Akimas Fortran code. A bilinear interpolator for regular grids was also added for comparison with the bicubic interpolator on regular grids.

Maintained by Albrecht Gebhardt. Last updated 3 years ago.

fortran

5 stars 4.48 score 2 dependents

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