Description Usage Arguments Value Examples

This function implements the Dikin Walk using the Hessian of the Log barrier function. Note that a $r$ of 1 guarantees that the ellipsoid generated won't leave our polytope $K$ (see Theorems online)

1 2 | ```
dikin_walk(A, b, x0 = list(), points, r = 1, thin = 1, burn = 0,
chains = 1)
``` |

`A` |
is the lhs of Ax <= b |

`b` |
is the rhs of Ax <= b |

`x0` |
is the starting point (a list of points) |

`points` |
is the number of points we want to sample |

`r` |
is the radius of the ellipsoid (1 by default) |

`thin` |
every thin-th point is stored |

`burn` |
the first burn points are deleted |

`chains` |
is the number of chains we run |

a list of chains of the sampled points, each chain being a matrix object with each column as a point

1 2 3 4 5 6 7 8 9 10 11 | ```
A <- rbind(c(1, 0), c(0, 1))
b <- c(1, 1)
sampled_points <- dikin_walk(A = A, b = b, points = 10, x0 = list(c(0.5,0.5)))
## Not run:
## note that this Ax <= b is different from Ax=b that the
## user specifies for walkr (see transformation section in vignette)
dikin_walk(A = A, b = b, x0, points = 100,
r = 1thin = 1, burn = 0, chains = 1)
## End(Not run)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.