# Control the parameters used to classify hotspots

Source:`R/hotspot_classify_params.R`

`hotspot_classify_params.Rd`

This function allows specification of parameters that affect the output from
`hotspot_classify`

.

## Usage

```
hotspot_classify_params(
hotspot_prop = 0.1,
persistent_prop = 0.8,
recent_prop = 0.2,
critical_p = 0.05,
nb_dist = NULL,
include_self = TRUE,
p_adjust_method = NULL
)
```

## Arguments

- hotspot_prop
A single numeric value specifying the minimum proportion of periods for which a cell must contain significant clusters of points before the cell can be classified as a hot or cold spot of any type.

- persistent_prop
A single numeric value specifying the minimum proportion of periods for which a cell must contain significant clusters of points before the cell can be classified as a persistent hot or cold spot.

- recent_prop
A single numeric value specifying the proportion of periods that should be treated as being recent in the classification of emerging and former hotspots.

- critical_p
A threshold

*p*-value below which values should be treated as being statistically significant.- nb_dist
The distance around a cell that contains the neighbours of that cell, which are used in calculating the statistic. If this argument is

`NULL`

(the default),`nb_dist`

is set as`cell_size * sqrt(2)`

so that only the cells immediately adjacent to each cell are treated as being its neighbours.- include_self
Should points in a given cell be counted as well as counts in neighbouring cells when calculating the values of

*G*_{i}^{*}(if`include_self = TRUE`

, the default) or*G*_{i}^{*}(if`include_self = FALSE`

) values? You are unlikely to want to change the default value.- p_adjust_method
The method to be used to adjust

*p*-values for multiple comparisons.`NULL`

(the default) uses the default method used by`p.adjust`

, but any of the character values in`stats::p.adjust.methods`

may be specified.

## Value

A list that can be used as the input to the `params`

argument to
`hotspot_classify`

.