The R package polyCub implements cubature (numerical integration) over polygonal domains. It solves the problem of integrating a continuously differentiable function f(x,y) over simple closed polygons.

For the special case of a rectangular domain along the axes, the cubature package is more appropriate (cf. CRAN Task View: Numerical Mathematics).


You can install polyCub from CRAN via:


To install the development version from the GitHub repository, use:

## install.packages("remotes")


The basic usage is:

polyCub(polyregion, f)

The polyCub() function by default calls polyCub.SV(), a C-implementation of product Gauss cubature. The various implemented cubature methods can also be called directly.

Implemented cubature methods

  1. polyCub.SV(): General-purpose product Gauss cubature (Sommariva and Vianello, 2007, BIT Numerical Mathematics,

  2. polyCub.midpoint(): Simple two-dimensional midpoint rule based on

  3. polyCub.iso(): Adaptive cubature for radially symmetric functions via line integrate() along the polygon boundary (Meyer and Held, 2014, The Annals of Applied Statistics,, Supplement B, Section 2.4)

  4. polyCub.exact.Gauss(): Accurate (but slow) integration of the bivariate Gaussian density based on polygon triangulation and mvtnorm::pmvnorm()

For details and illustrations see the vignette("polyCub") in the installed package or on CRAN.


The polyCub package evolved from the need to integrate so-called spatial interaction functions (Gaussian or power-law kernels) over the observation region of a spatio-temporal point process. Such epidemic models are implemented in surveillance.


Contributions are welcome! Please submit suggestions or report bugs at or via e-mail to maintainer("polyCub").


The polyCub package is free and open source software, licensed under the GPLv2.

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polyCub documentation built on Nov. 28, 2022, 5:21 p.m.