Bayesian journey to crime — bjtc • crimlab

Combines a journey-to-crime surface over origin zones with an origin-destination matrix of solved offences (Levine 2009; Levine and Block 2011): P(Jtc), the surface; P(O), the origins of all solved offences; P(O|Jtc), the origins of offences in the zones where the series happened; their product, Bayes' numerator with the surface as prior; and the risk, the product over P(O), renormalised. Each block sums to 1. The matrix describes past solved offences and inherits their selection.

Usage

bjtc(pj, od, dest)

Arguments

pj: The journey-to-crime value of each origin zone: numbers from 0, not all 0.
od: The origin-destination counts: a matrix with one row per origin zone and one column per destination zone, numbers from 0.
dest: The destination zone (column of od) of each incident of the series: whole numbers from 1; repeats count.

Value

A data frame with one row per origin zone: pj, po, pod, prod and risk (0 where po is 0).

References

Levine, N. and Block, R. (2011). Bayesian journey-to-crime estimation: an improvement in geographic profiling methodology. The Professional Geographer, 63(2), 213-229. doi:10.1080/00330124.2010.547152

Examples

od <- matrix(c(5, 1, 0, 2, 4, 1, 0, 1, 6), 3)
bjtc(pj = c(0.5, 0.3, 0.2), od = od, dest = c(1, 2, 2))
#>    pj   po  pod       prod       risk
#> 1 0.5 0.35 0.45 0.59210526 0.55900621
#> 2 0.3 0.30 0.45 0.35526316 0.39130435
#> 3 0.2 0.35 0.10 0.05263158 0.04968944