Calculates the total motif counts for a given model, in terms of the number of times each motif appears in the data.
motif_census(m, locs)An object of class DEFM.
Idx (starting from zero) with the variables that will be included in the census.
A matrix of class defm_motif_census with the motif counts.
Vega Yon, G. G., Pugh, M. J., & Valente, T. W. (2022). Discrete Exponential-Family Models for Multivariate Binary Outcomes (arXiv:2211.00627). arXiv. https://arxiv.org/abs/2211.00627
# Loading Valente's SNS data
data(valentesnsList)
mymodel <- new_defm(
id = valentesnsList$id,
Y = valentesnsList$Y,
X = valentesnsList$X,
order = 1
)
# Adding the intercept terms and a motif from tobacco to mj
term_defm_logit_intercept(mymodel)
term_defm_transition_formula(mymodel, "{y1, 0y2} > {y1, y2}")
# Initialize the model
init_defm(mymodel)
# Motif counts featuring only the first two variables
motif_census(mymodel, locs = 0:1)
#> Motif census for variable set: {alcohol, tobacco}
#> Motif Total
#> 1 {0, 0} > {0, 0} * 642
#> 2 {1, 0} > {1, 0} * 273
#> 3 {0, 0} > {1, 0} 110
#> 4 {1, 0} > {1, 1} 45
#> 5 {1, 1} > {1, 1} * 33
#> 6 {0, 0} > {1, 1} 25
#> 7 {0, 0} > {0, 1} 14
#> 8 {0, 1} > {1, 1} 11
#> 9 {0, 1} > {0, 1} * 8
#> (*): No change