Estimate Classic Markov Transition Dynamics — markov

Estimates transition counts and probabilities between adjacent periods for a classified long panel.

Usage

markov_dynamics(classes, id, time, state = class)

Arguments

classes: A classified data frame from classify_dynamics() or any data frame with ID, time, and state columns.
id, time, state: Columns identifying spatial unit, time, and state.

Value

A grd_markov object.

Examples

panel <- data.frame(
  id = rep(letters[1:4], each = 3),
  year = rep(2020:2022, times = 4),
  value = c(8, 9, 11, 10, 12, 13, 15, 14, 16, 20, 22, 25)
)

classes <- classify_dynamics(panel, id, year, value, k = 3)
markov <- markov_dynamics(classes, id, year, class)

markov
#> <grd_markov>
#> 3 states, 8 observed transitions
#>     
#>             Q1        Q2        Q3
#>   Q1 0.6666667 0.3333333 0.0000000
#>   Q2 0.0000000 0.6666667 0.3333333
#>   Q3 0.0000000 0.0000000 1.0000000
transition_matrix(markov)
#>     
#>             Q1        Q2        Q3
#>   Q1 0.6666667 0.3333333 0.0000000
#>   Q2 0.0000000 0.6666667 0.3333333
#>   Q3 0.0000000 0.0000000 1.0000000
steady_state(markov)
#> Q1 Q2 Q3 
#>  0  0  1