expperm-package {expperm} | R Documentation |

A set of functions for computing expected permutation matrices given a matrix of likelihoods for each individual assignment. It has been written to accompany the forthcoming paper 'Computing expectations and marginal likelihoods for permutations'. Publication details will be updated as soon as they are finalized.

The DESCRIPTION file:

Package: | expperm |

Type: | Package |

Title: | Computing Expectations and Marginal Likelihoods for Permutations |

Version: | 1.6 |

Date: | 2019-05-23 |

Author: | Ben Powell |

Maintainer: | Ben Powell <ben.powell@york.ac.uk> |

Description: | A set of functions for computing expected permutation matrices given a matrix of likelihoods for each individual assignment. It has been written to accompany the forthcoming paper 'Computing expectations and marginal likelihoods for permutations'. Publication details will be updated as soon as they are finalized. |

License: | GPL-3 |

Depends: | R (>= 2.10) |

Imports: | Rcpp (>= 1.0.1) |

LinkingTo: | Rcpp |

LazyData: | true |

RoxygenNote: | 6.1.1 |

Suggests: | testthat |

Index of help topics:

A A small random matrix BG The Brualdi-Gibson method for computing an expected permutation matrix BG_cpp The Brualdi-Gibson method for computing an expected permutation matrix using C++ brute Brute-force calculation of an expected permutation matrix brute_cpp Brute-force calculation of an expected permutation matrix using C++ df1 A small data frame of simulated records df2 A (second) small data frame of simulated records expperm-package Computing Expectations and Marginal Likelihoods for Permutations is.tridiagonal Checking a matrix is tridiagonal ryser The Ryser method for computing an expected permutation matrix ryser_cpp The Ryser method for computing an expected permutation matrix using C++ sink A variational approximation of an expected permutation matrix sink_cpp A variational approximation of an expected permutation matrix using C++ triA A small random tridiagonal matrix

The package serves primarily to demonstrate the algorithms described in the accompanying paper, which is currently under review.

We include versions, which are as similar as reasonably possible, of algorithms written in both R and C++. The R code is intended to facilitate testing, modification and re-use of the code while the C++ code is intended to implement the algorithms most efficiently for application to real problems.

Ben Powell

Maintainer: Ben Powell <ben.powell@york.ac.uk>

Powell B., Smith P.A. (2019). "Computing expectations and marginal likelihoods for permutations." (In Submission).

[Package *expperm* version 1.6 Index]