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mobilityIndexR measures mobility in a population by generating transition matrices and calculating mobility indices.
# Install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("bcmullins/mobilityIndexR")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 262909.3195Using 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] 0.58These 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.