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crimelinkage (version 0.0.3)

Statistical Methods for Crime Series Linkage

Description

Statistical Methods for Crime Series Linkage. This package provides code for criminal case linkage, crime series identification, crime series clustering, and suspect identification.

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Version

Install

install.packages('crimelinkage')

Monthly Downloads

22

Version

0.0.3

License

GPL-3

Maintainer

Michael Porter

Last Published

April 18th, 2015

Functions in crimelinkage (0.0.3)

getCrimeSeries

Generate a list of offenders and their associated crime series.
crimes

Ficticious dataset of crime events
predictNB

Generate prediction (sum of log bayes factors) from a naiveBayes object
fixDateTime

Updates criminal incident data with date-time objects in correct format.
compareSpatial

Make spatial evidence variables
getCrimes

Generate a list of crimes for a specific offender
catLevels

Make levels for merging category predictors
predictBF

Generate prediction of a component bayes factor
plotBKG

Generate a background plot
getCriminals

Lookup the offenders responsible for a set of solved crimes
makePairs

Generates indices of linked and unlinked crime pairs (with weights)
make.breaks

Make break points for binning continuous predictors
clusterPath

Follows path of one crime up a dendrogram
offenders

Ficticious offender data
linkage

Hierarchical Based Linkage
makeSeriesData

Make crime series data
crimeClust_hier

Agglomerative Hierarchical Crime Series Clustering
color

Creates transparent colors
crimelinkage-package

crimelinkage package: Statistical Methods for Crime Series Linkage
plot_hcc

Plot a hierarchical crime clustering object
getDateTime

Creates date-time objects for censored crime data
plotBF

plots 1D bayes factor
getBF

Estimates the bayes factor for continous and categorical predictors.
compareCrimes

Creates evidence variables by calculating distance between crime pairs
bayesPairs

Extracts the crimes with the largest probability of being linked.
compareNumeric

Make evidence variables from numeric crime data
dtdiff

Calculates time between two vectors of datetimes
crimeClust_bayes

Bayesian model-based partially-supervised clustering for crime series identification
getROC

Cacluate ROC like metrics.
seriesID

Crime series identification
compareCategorical

Make evidence variables from categorical crime data
compareTemporal

Make temporal evidence variable from (possibly uncertain) temporal info
makeGroups

Generates crime groups from crime series data
naiveBayes

Naive bayes classifier using histograms and shrinkage