Description Usage Arguments Value Author(s) References

Compute a binned approximation of the data on a regularly spaced grid using the multivariate linear binning rule described in Wand (1994).

1 | ```
mvlinbin(X, r = 7, padding)
``` |

`X` |
a numeric matrix. |

`r` |
a positive integer value. The number of grid points |

`padding` |
a numeric vector of positive values with length equal to the number of columns of |

a list with class `mvlinbin`

containing the following elements.

`axes` |
a numeric matrix whose columns contain the grid points used along each axis to bin the data. |

`xi` |
a numeric array containing the binned approximation of the data. |

`X` |
a numeric matrix containing the input data. |

`deltas` |
a numeric vector containing the grid spacing. |

`M` |
an integer value giving the number of grid points used in each coordinate direction. |

`n` |
an integer value containing the number of data points binned. |

`d` |
an integer value giving the dimensionality of the data. |

Kjell Konis [email protected]

Wand, M. P. (1994). Fast Computation of Multivariate Kernel Estimators. *Journal of Computational and Graphical Statistics*, 3, 433-445.

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