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mobilityIndexR

AppVeyor build status

mobilityIndexR measures mobility in a population by generating transition matrices and calculating mobility indices.

Installation

# Install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("bcmullins/mobilityIndexR")

Basic Usage

Let’s use one of the built in datasets to create a transition matrix:

library(mobilityIndexR)
data("incomeMobility")
getTMatrix(dat = incomeMobility, col_x = 't0', col_y = 't5', type = 'relative', probs = TRUE, num_ranks = 5)
#> $tmatrix
#>    
#>         1     2     3     4     5
#>   1 0.152 0.040 0.008 0.000 0.000
#>   2 0.048 0.080 0.048 0.024 0.000
#>   3 0.000 0.048 0.064 0.056 0.032
#>   4 0.000 0.008 0.024 0.120 0.048
#>   5 0.000 0.024 0.056 0.000 0.120
#> 
#> $col_x_bounds
#>      0%     20%     40%     60%     80%    100% 
#>   462.0 21543.4 42469.8 64061.6 77888.4 99557.0 
#> 
#> $col_y_bounds
#>          0%         20%         40%         60%         80%        100% 
#>    340.2705  18204.9969  39710.3062  58494.6271  78178.6713 262909.3195

Using this data, let’s now calculate mobility indices:

  library(mobilityIndexR)
  data("incomeMobility")
  getMobilityIndices(dat = incomeMobility, col_x = 't0', col_y = 't5', type = 'relative', num_ranks = 5)
#> $average_movement
#> [1] 0.64
#> 
#> $os_far_bottom
#> [1] 0.04
#> 
#> $os_far_top
#> [1] 0.4
#> 
#> $os_total_bottom
#> [1] 0.24
#> 
#> $os_total_top
#> [1] 0.4
#> 
#> $prais_bibby
#> [1] 0.464
#> 
#> $wgm
#> [1] 0.58

More examples coming soon!

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.