Nothing
README.md
In MLID: Multilevel Index of Dissimilarity
About
The MLID package provides tools and functions for studying ethnic and social segregation with a multilevel index of dissimilarity that measures uneveness, spatial clustering and scale differences simultaneously.
Installation
To get the latest version on CRAN:
installed.packages("MLID")
To get the current development version from GitHub:
# install.packages("devtools")
require(devtools)
devtools::install_github("profrichharris/MLID")
Using MLID
For a quick introduction, follow the examples provided with
?id
For a tutorial
vignette("MLID", package = "MLID")
Licence
Scripts are released under the GPL-3 License
Try the MLID package in your browser
Any scripts or data that you put into this service are public.
MLID documentation built on May 2, 2019, 11:05 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
About
The MLID package provides tools and functions for studying ethnic and social segregation with a multilevel index of dissimilarity that measures uneveness, spatial clustering and scale differences simultaneously.
Installation
To get the latest version on CRAN:
installed.packages("MLID")
To get the current development version from GitHub:
# install.packages("devtools")
require(devtools)
devtools::install_github("profrichharris/MLID")
Using MLID
For a quick introduction, follow the examples provided with
?id
For a tutorial
vignette("MLID", package = "MLID")
Licence
Scripts are released under the GPL-3 License
Try the MLID package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.