neutral_hotspots: neutral_hotspots
In mpadge/hotspotr: Compare Spatial Structure of Hotspots with Neutral Models

Description Usage Arguments Value See Also Examples

Implements neutral model of hotspot values and associated autocorrelation statustics. Current version is a simply internal R loop, while neutral_hotspots_ntests is a parallel version of exactly the same thing.

1 2	neutral_hotspots(nbs, wts, alpha = 0.1, sd0 = 0.1, ac_type = "moran", niters = 1, log_scale = TRUE, ntests = 100, parallel = FALSE, seed)

`nbs`	An `spdep` `nb` object listing all neighbours of each point
`wts`	Weighting factors for each neighbour; must have same length as nbs. Uniform weights used if not given.
`alpha`	strength of spatial autocorrelation
`sd0`	Standard deviation of truncated normal distribution used to model environmental variation (with mean of 1)
`ac_type`	Type of autocorrelation statistic to use in tests (`moran`, `geary`, or `getis-org`=`go`)
`niters`	Number of successive layers of spatial autocorrelation
`log_scale`	If TRUE, raw hotspot values are log-transformed
`ntests`	Number of tests over which to generate an average result
`parallel`	If true, the tests are conducted using the `R` package `parallel`, otherwise using (non-parallel) codeRcpp loops.
`seed`	Random seed

A vector of hotspot values sorted from high to low

ives

# First set up a grid of rectangular neighbours
size <- 10
xy <- cbind (rep (seq (size), each=size), rep (seq (size), size))
dhi <- 1 # for rook; dhi=1.5 for queen
nbs <- spdep::dnearneigh (xy, 0, dhi)
dat <- neutral_hotspots (nbs, ntests=1000)