Produce a new index table by taking all possible pairwise combinations of the input tables. This is useful for producing product models that expand model components through stratification.
Arguments
- ...
Index tables (see
mp_index).
See also
Other functions that return index tables
mp_index(),
mp_rename(),
mp_subset(),
mp_union()
Other functions that take products of index tables and return one index tables
mp_linear(),
mp_square(),
mp_symmetric(),
mp_triangle()
Examples
mp_cartesian(
mp_index(Epi = c("S", "I")),
mp_index(Age = c("young", "old"))
)
#> Epi Age
#> S young
#> I young
#> S old
#> I old
si = mp_index(Epi = c("S", "I"))
age = mp_index(Age = c("young", "old"))
loc = mp_index(City = c("hamilton", "toronto"))
vax = mp_index(Vax = c("unvax", "vax"))
(si
|> mp_cartesian(age)
|> mp_cartesian(loc)
|> mp_cartesian(vax)
)
#> Epi Age City Vax
#> S young hamilton unvax
#> I young hamilton unvax
#> S old hamilton unvax
#> I old hamilton unvax
#> S young toronto unvax
#> I young toronto unvax
#> S old toronto unvax
#> I old toronto unvax
#> S young hamilton vax
#> I young hamilton vax
#> S old hamilton vax
#> I old hamilton vax
#> S young toronto vax
#> I young toronto vax
#> S old toronto vax
#> I old toronto vax
flow_rates = mp_index(Epi = c("infection", "recovery"))
mp_union(
mp_cartesian(
mp_subset(flow_rates, Epi = "infection"),
age
),
mp_subset(flow_rates, Epi = "recovery")
)
#> Epi Age
#> infection young
#> infection old
#> recovery