Compares the complete bivariate patterns C, D1–D4, and E1–E4 using AIC and returns the selected pattern.
Arguments
- empirical
An empirical bivariate count matrix with 16 rows and 2 columns, as returned by
countEmpBivariate.
Value
A list with class c("dyadic_pattern", "list") containing
components aic (a data frame with columns pattern,
matrix, and aic), pattern (the selected pattern
label), and call. It remains usable as an ordinary list. When
empirical was created by countEmpBivariate(), its stored
sequence metadata is propagated so that plot() can display the four
observed state strips.
Details
Conditional on the complete bivariate case, the G-squared deviance is computed for each C, D1–D4, and E1–E4 candidate before calculating $$AIC = G^2 + 2k,$$ where $$G^2 = 2 \sum_{ij} O_{ij} \log(O_{ij} / E_{ij}).$$ The candidate with the smallest AIC is selected. If candidates have exactly equal AIC values, the first candidate in the documented comparison order is selected.
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
)
completePattern(emp)
#> Dyadic interaction pattern
#> Pattern: complete partner only (E1)