Plot an image of tessellation residuals for a space-time point process.

1 2 | ```
## S3 method for class 'tessresid'
plot(x, ..., col.key = rev(heat.colors(100)), cutoffs = NULL)
``` |

`x` |
A “ |

`...` |
Arguments for use with |

`col.key` |
A vector of colors in hexadecimal format. |

`cutoffs` |
A vector of cut points for assigning the colors in |

`cutoffs`

must be a vector of increasing values of the same length as `col.key`

plus 1. `cutoffs`

divides the residual values in `x$residuals`

into a number of intervals equal to the number of colors in `col.key`

. The colors are assigned to the intervals in order, e.g. the first color in `col.key`

will be plotted in the cells defined by the tessellation in `x$tile.list`

that contains a residual that falls anywhere in the first interval (lower bound inclusive, upper bound exclusive).

Default `col.key`

is a vector of 100 `heat`

colors in reverse. Default `cutoffs`

is a vector of 101 equally spaced points that range from the minimum residual in `x$residuals`

, minus a very small number, to the maximum residual, plus a very small number.

The default `col.key`

and `cutoffs`

may not be useful if the residuals are highly skewed. In this case, there should be more values in `cutoffs`

where the residuals are most dense.

These are simply default plots for quick illustration of the residuals, and may or may not be useful for detailed analysis of the residuals.

Robert Clements

1 2 3 4 5 6 7 | ```
data(tsresiduals)
plot(tsresiduals)
hist(tsresiduals$residuals)
cutoffs = c(seq(-1.07, -.51, length.out = 15), seq(-.5, .5, length.out=70),
seq(.51, 2.42, length.out = 16))
plot(tsresiduals, cutoffs = cutoffs)
``` |

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