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rcrimeanalysis
View on CRAN: Click
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Download and install rcrimeanalysis package within the R console
Install from CRAN:
install.packages("rcrimeanalysis")
Install from Github:
library("remotes")
install_github("cran/rcrimeanalysis")
Install by package version:
library("remotes")
install_version("rcrimeanalysis", "0.5.0")
Attach the package and use:
library("rcrimeanalysis")
Maintained by
Jamie Spaulding
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-12-01
Latest Update: 2023-05-18
Description:
An implementation of functions for the analysis of crime incident or records management system data. The package implements analysis algorithms scaled for city or regional crime analysis units. The package provides functions for kernel density estimation for crime heat maps, geocoding using the 'Google Maps' API, identification of repeat crime incidents, spatio-temporal map comparison across time intervals, time series analysis (forecasting and decomposition), detection of optimal parameters for the identification of near repeat incidents, and near repeat analysis with crime network linkage.
How to cite:
Jamie Spaulding (2019). rcrimeanalysis: An Implementation of Crime Analysis Methods. R package version 0.5.0, https://cran.r-project.org/web/packages/rcrimeanalysis
Previous versions and publish date:
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Functions, R codes and Examples using
the rcrimeanalysis R package
Some associated functions: crimes . geocode_address . id_repeat . kde_int_comp . kde_map . near_repeat_analysis . near_repeat_eval . ts_daily_decomp . ts_forecast . ts_month_decomp .
Some associated R codes: crimes.R . geocode_address.R . id_repeat.R . kde_int_comp.R . kde_map.R . near_repeat_analysis.R . near_repeat_eval.R . ts_daily_decomp.R . ts_forecast.R . ts_month_decomp.R . Full rcrimeanalysis package functions and examples
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