migest (version 1.3)

cm3: Conditional Maximisation Routine for the Indirect Estimation of Origin-Destination-Migrant Type Migration Flow Tables with Known Origin and Destination Margins.

Description

The cm3 function finds the maximum likelihood estimates for parameters in the log-linear model: $$\log y_{ijk} = \log \alpha_{i} + \log \beta_{j} + \log m_{ijk}$$ as introduced by Abel (2005). The $\alpha_{i}$ and $\beta_{j}$ represent background information related to the characteristics of the origin and destinations respectively. The $m_{ijk}$ factor represents auxiliary information on origin-destination migration flows by a migrant characteristic (such as age, sex, disability, household type, economic status, etc.). This method is useful for combining data from detailed data collection processes (such as a Census) with more up-to-date information on migration inflows and outflows (where details on movements by migrant characteristics are not known).

Usage

cm3(rtot = NULL, ctot = NULL, m, tol = 1e-05, maxit = 500, iter = FALSE)

Arguments

rtot

Origin (row) totals to constrain indirect estimates to.

ctot

Destination (column) totals to constrain indirect estimates to.

m

Array of auxiliary data. By default set to 1 for all origin-destination-migrant type combinations.

tol

Tolerance level for parameter estimation.

maxit

Maximum number of iterations for parameter estimation.

iter

Print the parameter estimates at each iteration. By default FALSE.

Value

• Returns a list object with:
• N
  Array of origin-destination matrices of indirect estimates
• theta
  Collection of parameter estimates

Details

Parameter estimates were obtained using the conditional maximisation of the likelihood, as discussed by Abel (2005) and Raymer et. al. (2007). The user must ensure that the row and column totals are equal in sum. Care must also be taken to allow the row and column dimension of the auxiliary matrix (m) to equal those provided in the row and column totals.

References

Abel, G. J. (2005) The Indirect Estimation of Elderly Migrant Flows in England and Wales (MS.c. Thesis). University of Southampton Raymer, J., G. J. Abel, and P. W. F. Smith (2007). Combining census and registration data to estimate detailed elderly migration flows in England and Wales. Journal of the Royal Statistical Society: Series A (Statistics in Society) 170 (4), 891--908.

See Also

cm2, ipf3

Examples

## over two tables
dn <- LETTERS[1:2]
y <- cm3(rtot = c(18, 20) * 2, ctot = c(16, 22) * 2, 
        m = array(c(5, 1, 2, 7, 4, 2, 5, 9), dim = c(2, 2, 2), 
        dimnames = list(orig = dn, dest = dn, type = c("ILL", "HEALTHY"))))
# display with row, col and table totals
round(addmargins(y$N))

## over three tables
y <- cm3(rtot = c(170, 120, 410), ctot = c(500, 140, 60), 
        m = array(c(5, 1, 2, 7, 4, 2, 5, 9, 5, 4, 3, 1), dim = c(2, 2, 3), 
        dimnames = list(orig = dn, dest = dn, type = c("0--15", "15-60", ">60"))),
        iter = FALSE)
# display with row, col and table totals
round(addmargins(y$N))