Creating observations of lists in a population
create_list_presences.RdThe function `create_list_presences` creates a matrix of presences based on a population of individuals and the matrix of presences.
Arguments
- pop
A baseline population from which one will select individuals to arrive and leave in a number of years.
- presences
A matrix of presences of all the individuals in the population for a number of years.
- formula_prob
A linear predictor formula to calculate the probability of appearing in such a list.
- coef_values
The values for each coefficient to be used in the linear predictor defined in `formula_prob`. The coefficients will be used considering a logit link function.
Value
A matrix with the information of the detection (1) or non detection (0) for each individual of the population considering a number of years of observation.
Examples
set.seed(111)
# creating main population
main_pop <- create_population(
size = 500,
n_cat_var = 3,
prob_bin = c(0.5))
# creating matrix of presences.
presences <- create_presences(main_pop,
formula_phi = ~ bin1,
coef_values = c(2, -1),
varying_arrival = TRUE,
const_rate_arrival = FALSE,
years = 3)
# creating list1 observation as a function of bin1
list1 <- create_list_presences(main_pop, presences,
~ bin1,
c(1.5, -0.5))
# checking the conditional distribution of list1 given bin1
prop.table(table(main_pop$bin1, list1[,1]), 1)
#>
#> 0 1
#> 0 0.6173285 0.3826715
#> 1 0.7040359 0.2959641
# creating list1 observation as a function of cat1, that needs two
# coefficients, because cat1 has 3 categories.
list2 <- create_list_presences(main_pop, presences,
~ cat1,
c(-0.5, -0.5, 1.0))
# checking the conditional distribution of list2 given bin1
prop.table(table(main_pop$bin1, list2[, 1]), 1)
#>
#> 0 1
#> 0 0.7978339 0.2021661
#> 1 0.8026906 0.1973094
# checking the conditional distribution of list2 given cat1
prop.table(table(main_pop$cat1, list2[, 1]), 1)
#>
#> 0 1
#> A 0.8117155 0.1882845
#> B 0.8600000 0.1400000
#> C 0.6936937 0.3063063