Description Usage Arguments Details Value Author(s) References Examples

It generates random rotations in three-dimensional space that follow a probability distribution, matrix Fisher distribution, arising in fitting and matching problem.

1 | ```
habeck.rot(F)
``` |

`F` |
An arbitrary 3 x 3 matrix represents the parameter matrix of this distribution. |

Firstly rotation matrices **X** are chosen which are the closest to F, and then parameterized using euler angles.
Then a Gibbs sampling algorithm is implemented to generate rotation matrices from the resulting disribution of
the euler angles.

A simulated rotation matrix.

Anamul Sajib<[email protected]>

R implementation and documentation: Anamul Sajib<[email protected]>

Habeck M (2009). Generation of three-dimensional random rotations in fitting and matching problems. Computational Statistics, 24, 719–731.

1 2 3 | ```
F <- 10^(-1) * matrix( c(85, 11, 41, 78, 39, 60, 43, 64, 48), ncol = 3 ) ## Arbitrary F matrix
X <- habeck.rot(F)
det(X)
``` |

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