Plot a scatter plot conditioned on a continuous variable, with marginal conditional density plots.

ScatterHistN( frame, xvar, yvar, zvar, title, ..., annot_size = 3, colorPalette = "RdYlBu", nclus = 3, adjust_x = 1, adjust_y = 1 )

frame | data frame to get values from |
---|---|

xvar | name of the x variable |

yvar | name of the y variable |

zvar | name of height variable |

title | title to place on plot |

... | no unnamed argument, added to force named binding of later arguments. |

annot_size | numeric: scale annotation text (if present) |

colorPalette | name of a Brewer palette (see https://colorbrewer2.org/ ) |

nclus | scalar: number of z-clusters to plot |

adjust_x | numeric: adjust x density plot |

adjust_y | numeric: adjust y density plot |

`xvar`

and `yvar`

are the coordinates of the points, and `zvar`

is the
continuous conditioning variable. `zvar`

is partitioned into `nclus`

disjoint
ranges (by default, 3), which are then treated as discrete categories.The scatterplot and marginal density plots
are color-coded by these categories.

set.seed(34903490) frm = data.frame(x=rnorm(50),y=rnorm(50)) frm$z <- frm$x+frm$y WVPlots::ScatterHistN(frm, "x", "y", "z", title="Example Joint Distribution")