ccp_net0: Cohort Component Population Projection Model based on a...
In gjabel/demoproj: Demographic Projection Models

Description Usage Arguments Value Examples

A cohort component projection model based on a closed population,

N(t+5) = L[t, t+1] ≤ft( N(t) + \frac{1}{2} M[t, t+1] \right) + \frac{1}{2} M[t, t+1]

where the Leslie matrix, eqnL, is created given user defined age specific fertility and survivorship rates.

ccp_net0(n = NULL, x = NULL, p = NULL, Nx_f = NULL, Nx_m = NULL,
  sx_f = NULL, sx_m = NULL, fx = NULL, sn_f = NULL, sn_m = NULL,
  sex_ratio = 1/(1 + 1.05), Mx_f = NULL, Mx_m = NULL,
  tidy_output = TRUE, age_lab = x, gender_lab = c("Female", "Male"), ...)

ccp_net(n = NULL, x = NULL, p = NULL, Nx_f = NULL, Nx_m = NULL,
  sx_f = NULL, sx_m = NULL, fx = NULL, sn_f = NULL, sn_m = NULL,
  sex_ratio = 1/(1 + 1.05), Mx_f = NULL, Mx_m = NULL,
  tidy_output = TRUE, age_lab = x, gender_lab = c("Female", "Male"), ...)

`n`	Numeric value for the number of projection steps.
`x`	Vector containing a character string of age group labels.
`p`	Numeric value for step size of the population projection.
`Nx_f, Nx_m`	Vectors containing numeric values of the initial female and male population size in each age group (`x`).
`sx_f, sx_m, fx, Mx_f, Mx_m`	Vectors containing numeric values of the age specific female and male survival and fertility rates and female and male net migration counts. If `ccp_net0` is used a single vector is required. If `ccp_net` is used a matrix of period specific rates (or counts for net migration) is required, where rows represent age groups (females in top rows, males in bottom rows) and columns future periods. If a single vector is passed to `ccp_net` a matrix based on constant assumptions in all future rates and net migration counts will be constructed.
`sn_f, sn_m, sex_ratio`	Numeric value of the female and male survivorship of new-born babies from birth to the end of the interval and the sex ratio at birth of new-born babies. If `ccp_net0` is used a single value is required. If `ccp_net` is used a vector of period specific values is required. If a single value is passed to `ccp_net` a vector based on constant assumptions in all future rates will be constructed.
`tidy_output`	Logical value to indicate if projection output should be in a tidy data format (`TRUE`, the default) or as a `matrix` where rows represent age and gender groups and columns the projection year.
`age_lab, gender_lab`	Vector containing a character string of age and gender group labels. Only used if projection output is in a tidy data format. See `tidy_pp` for more details.
`...`	Additional arguments passed to `tidy_pp` to build a tidy data frame (if chosen from `tidy_output`).

Projected populations by age and gender for n future steps, given the fertility and survivorship rates and net migration counts. Depending on the tidy_output value the projections will be returned as either a matrix or a tibble. Both versions contain the initial population sizes given in Nx.

ccp_net0 produces population projections based strictly on constant future rates.

ccp_net produces population projections based non-constant future rates.

library(dplyr)
df0 <- sweden1993 %>%
   # set male net migration to the same as female
   mutate(Mx_m = Mx_f)

# matrix output
ccp_net0(n = 5, x = df0$x, p = 5,Nx_f = df0$Nx_f, Nx_m = df0$Nx_m,
         sx_f = df0$sx_f, sx_m = df0$sx_m,
         fx = df0$fx, sn_f = df0$Lx_f[1]/(5*100000), sn_m = df0$Lx_m[1]/(5*100000),
         Mx_f = df0$Mx_f, Mx_m = df0$Mx_m,
         tidy_output = FALSE)

# tidy data frame output
ccp_net0(n = 5, x = df0$x, p = 5,Nx_f = df0$Nx_f, Nx_m = df0$Nx_m,
         sx_f = df0$sx_f, sx_m = df0$sx_m,
         fx = df0$fx, sn_f = df0$Lx_f[1]/(5*100000), sn_m = df0$Lx_m[1]/(5*100000),
         Mx_f = df0$Mx_f, Mx_m = df0$Mx_m,
         year0 = 1993, age_lab = df0$age)

# setting up non-constant future male net migrant counts
MM <- matrix(df0$Mx_m, nrow = length(df0$Mx_m), ncol = 5)
MM <- sweep(MM, 2, seq(from = 1, to = 1.5, length = 5), "*")
# net migration increase
colSums(MM)
# run projection with increasing net migration, fx and sx remains constant
ccp_net(n = 5, x = df0$x, p = 5, Nx_f = df0$Nx_f, Nx_m = df0$Nx_m,
        sx_f = df0$sx_f, sx_m = df0$sx_m,
        fx = df0$fx, sn_f = df0$Lx_f[1]/(5*100000), sn_m = df0$Lx_m[1]/(5*100000),
        Mx_f = df0$Mx_f, Mx_m = MM,
        tidy_output = FALSE)