Description Usage Arguments Details Value Note Author(s) References See Also Examples

Optimal kernel widths output by `ma`

are employed to
recompute the weighted joint distribution for two variables in
a data set, and a contour plot for this distribution is drawn.

1 | ```
pd(d,iv=1,jv=2)
``` |

`d` |
an n x m data frame with m > 1. |

`iv` |
the column index of the independent variable |

`jv` |
the column index of the dependent variable |

A data set of two variables is extracted from the user's data set and a
full distribution is calculated
using weighted marginal and joint likelihoods. The optimal kernel sizes and
weighting are first computed via a call to `ma`

.

An n x n distribution of weighted likelihoods is returned.

The data set must contain at least 2 columns.

Ben Murrell, Dan Murrell & Hugh Murrell.

Discovering general multidimensional associations, http://arxiv.org/abs/1303.1828

1 2 3 4 5 6 |

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