nb_scale_global {migest}

Scale native born populations to match global differences in births and deaths over period

Description

This function is predominantly intended to be used within the ffs routines in the migest package. Adjustment to ensure that global differences in stocks match the global demographic changes from births and deaths.

Usage

nb_scale_global(m1, m2, b, d, verbose = FALSE)

Arguments

m1

Matrix of migrant stock totals at time t. Rows in the matrix correspond to place of birth and columns to place of residence at time t

m2

Matrix of migrant stock totals at time t+1. Rows in the matrix correspond to place of birth and columns to place of residence at time t+1.

b

Vector of the number of births between time t and t+1 in each region.

d

Vector of the number of deaths between time t and t+1 in each region.

verbose

Logical value to indicate the print the parameter estimates at each iteration. By default FALSE.

Value

List with adjusted m1 and m2.

Author(s)

Guy J. Abel

See Also

ffs_demo

Examples

## cant have examples if function not in namespace - i.e. without export 
## so comment all out for own use
# r <- LETTERS[1:4]
# P1 <- matrix(data = c(1000, 100, 10, 0, 55, 555, 50, 5, 80, 40, 800, 40, 20, 25, 20, 200),
#              nrow = 4, ncol = 4, dimnames = list(birth = r, dest = r), byrow = TRUE)
# P2 <- matrix(data = c(950, 100, 60, 0, 80, 505, 75, 5, 90, 30, 800, 40, 40, 45, 0, 180),
#              nrow = 4, ncol = 4, dimnames = list(birth = r, dest = r), byrow = TRUE)
# # display with row and col totals
# addmargins(A = P1)
# addmargins(A = P2)
# 
# # births and deaths
# b <- rep(x = 10, 4)
# d <- rep(x = 5, 4)
# # no change in stocks, but 20 more births than deaths...
# sum(P2) - sum(P1) + sum(d) - sum(b)
# # scale
# y <- nb_scale_global (m1 = P1, m2 = P2, b = b, d = d)
# y
# sum(y$m2_adj) - sum(y$m1_adj) + sum(d) - sum(b)
# 
# # check for when extra is positive and odd
# d[1] <- 32
# d
# sum(P2 - P1) - sum(b - d)
# # scale
# y <- nb_scale_global(m1 = P1, m2 = P2, b = b, d = d)
# sum(y$m2_adj) - sum(y$m1_adj) + sum(d) - sum(b)