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and Transportation","monthly_downloads":0,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"---\noutput: github_document\n---\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# accessibility \u003cimg align=\"right\" src=\"man/figures/logo.png\" alt=\"logo\" width=\"180\"\u003e\n\n[![CRAN\nstatus](https://www.r-pkg.org/badges/version/accessibility)](https://CRAN.R-project.org/package=accessibility)\n[![rcmdcheck](https://github.com/ipeaGIT/accessibility/workflows/rcmdcheck/badge.svg)](https://github.com/ipeaGIT/accessibility/actions)\n[![CRAN/METACRAN Total\ndownloads](https://cranlogs.r-pkg.org/badges/grand-total/accessibility?color=yellow)](https://CRAN.R-project.org/package=accessibility)\n[![Codecov test\ncoverage](https://codecov.io/gh/ipeaGIT/accessibility/branch/main/graph/badge.svg)](https://app.codecov.io/gh/ipeaGIT/accessibility?branch=main)\n[![Lifecycle:\nstable](https://lifecycle.r-lib.org/articles/figures/lifecycle-stable.svg)](https://lifecycle.r-lib.org/articles/stages.html)\n\n**accessibility** offers a set of fast and convenient functions to help\nconducting accessibility analyses. Given a pre-computed travel cost matrix and a\nland use dataset (containing the location of jobs, healthcare and population,\nfor example), the package allows one to calculate accessibility levels and\naccessibility poverty and inequality. The package covers the majority of the\nmost commonly used accessibility measures (such as cumulative opportunities,\ngravity-based and floating catchment areas methods), some cutting edge measures \nproposed in the literature (e.g. balancing cost and constrained accessibility),\nas well as the most frequently used inequality and poverty metrics (such as the \nPalma ratio, the concentration and Theil indices and the FGT family of measures).\n\n## Installation\n\nStable version:\n\n```{r, eval = FALSE}\ninstall.packages(\"accessibility\")\n```\n\nDevelopment version:\n\n```{r, eval = FALSE}\n# install.packages(\"remotes\")\nremotes::install_github(\"ipeaGIT/accessibility\")\n```\n\n## Usage\n\nThis section aims to present a very brief overview of some of the packages'\nfeatures. Fore more details please read the vignettes:\n\n- [Introduction to **accessibility**: calculating accessibility\n  measures](https://ipeagit.github.io/accessibility/articles/accessibility.html)\n- [Decay\n  functions](https://ipeagit.github.io/accessibility/articles/decay_functions.html)\n- [Calculating accessibility inequality and\n  poverty](https://ipeagit.github.io/accessibility/articles/inequality_and_poverty.html)\n\nTo calculate accessibility levels, one simply needs a pre-calculated travel\nmatrix and some land use data. Below we showcase some of the available\nfunctions:\n\n```{r}\nlibrary(accessibility)\n\ndata_dir \u003c- system.file(\"extdata\", package = \"accessibility\")\ntravel_matrix \u003c- readRDS(file.path(data_dir, \"travel_matrix.rds\"))\nland_use_data \u003c- readRDS(file.path(data_dir, \"land_use_data.rds\"))\n\ncum_cutoff \u003c- cumulative_cutoff(\n  travel_matrix,\n  land_use_data,\n  opportunity = \"jobs\",\n  travel_cost = \"travel_time\",\n  cutoff = 30\n)\nhead(cum_cutoff)\n\ngrav \u003c- gravity(\n  travel_matrix,\n  land_use_data,\n  opportunity = \"schools\",\n  travel_cost = \"travel_time\",\n  decay_function = decay_exponential(decay_value = 0.2)\n)\nhead(grav)\n\nfca \u003c- floating_catchment_area(\n  travel_matrix,\n  land_use_data,\n  opportunity = \"jobs\",\n  travel_cost = \"travel_time\",\n  demand = \"population\",\n  method = \"2sfca\",\n  decay_function = decay_binary(cutoff = 50)\n)\nhead(fca)\n```\n\nCalculating inequality and poverty levels is equally easy. 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