Computes statistics.
Arguments
- formula
A model `formula` object. The left-hand side should be the name of a
iglm.dataobject available in the calling environment. Alternatively, the left-hand side can be aiglm.data.listobject to compute statistics for multipleiglm.dataobjects at once (is, e.g., the normal outcome of all simulations). Seeiglm-termsfor details on specifying the right-hand side terms.- canonical_names
(logical) If `TRUE`, returns canonical term names without label substitution. Default is `FALSE`.
Value
A named numeric vector (or matrix if a list of data objects is provided). Each element corresponds to a term in the
`formula`, and its value is the calculated observed feature
for that term based on the data in the iglm.data object. The names of the
vector match the (optionally labeled) term names derived from the formula terms.
Examples
# Create a iglm.data object
n_actor <- 10
neighborhood <- matrix(1, nrow = n_actor, ncol = n_actor)
type_x <- "binomial"
type_y <- "binomial"
x_attr_data <- rbinom(n_actor, 1, 0.5)
y_attr_data <- rbinom(n_actor, 1, 0.5)
z_net_data <- matrix(0, nrow = n_actor, ncol = n_actor)
object <- iglm.data(
z_network = z_net_data, x_attribute = x_attr_data,
y_attribute = y_attr_data, neighborhood = neighborhood,
directed = FALSE, type_x = type_x, type_y = type_y,
label_x = "age", label_y = "income"
)
statistics(object ~ edges(mode = "local") + attribute_y + attribute_x)
#> edges(mode = 'local') attribute_income attribute_age
#> 0 4 4
statistics(object ~ edges(mode = "local") + attribute_y + attribute_x, canonical_names = TRUE)
#> edges(mode = 'local') attribute_y attribute_x
#> 0 4 4
