Empirical transition counts for bivariate dyadic sequences

Computes empirical transition counts for bivariate categorical dyadic sequences with two variables. This function currently supports states = 2 only.

Usage

countEmpBivariate(chainFM_V1, chainSM_V1, chainFM_V2, chainSM_V2, states = 2L)

Arguments

chainFM_V1, chainSM_V1

Vectors of observed states for variable 1 for the first and second member.

chainFM_V2, chainSM_V2

Vectors of observed states for variable 2 for the first and second member.

states

A single integer. Currently only 2 is supported. Default is 2.

Value

An integer matrix with class c("dyadic_counts", "matrix", "array") with 16 rows and 2 columns when states = 2. It remains usable as an ordinary matrix.

Details

The bivariate counter currently supports states = 2 only. Rows represent the previous dyadic states of variable 1 and variable 2. The implementation uses the row mapping states^2 * (states * (FM_V1,t - 1) + (SM_V1,t - 1)) + states * (FM_V2,t - 1) + (SM_V2,t - 1) + 1. Columns correspond to the state of the first member on variable 1 at the next time point, \(FM_{V1,t+1}\).

Examples

chainFM_V1 <- c(1L, 2L, 1L, 2L, 2L, 1L)
chainSM_V1 <- c(2L, 1L, 2L, 1L, 1L, 2L)
chainFM_V2 <- c(1L, 1L, 2L, 2L, 1L, 2L)
chainSM_V2 <- c(2L, 2L, 1L, 1L, 2L, 1L)
emp <- countEmpBivariate(
  chainFM_V1, chainSM_V1, chainFM_V2, chainSM_V2,
  states = 2L
)
dim(emp)
#> [1] 16  2