RASbound

Bounded RAS (biproportional matrix balancing, also called iterative proportional fitting or raking) with lower and upper bounds on individual cells.

Classic RAS adjusts a seed matrix so that its row and column sums match given targets. RASbound adds cell-level bounds, for example when updating or regionalizing an input-output table and some cells must stay within a plausible range. If no matrix satisfies both the targets and the bounds, the functions say so, and tell you which rows and columns are involved.

Main functions

Function	What it does
`ras()`	Classic RAS, no bounds
`bras_freeze_sim()`, `bras_freeze_seq()`, `bras_freeze_hybrid()`	Bounded RAS that solves, fixes violating cells at their bound, and repeats. Margins are matched exactly and bounds are respected. `bras_freeze_hybrid()` is the recommended default.
`bras_naive()`, `bras_soft()`, `bras_cap_iter()`	Simpler reference methods, for comparison
`bras_calibrate_logit()`, `bras_calibrate_linear()`, `bras_calibrate_raking()`	Wrappers around `survey::calibrate()` (need the `survey` and `MASS` packages)

All functions take the same arguments and return an object of class bras_fit.

Example

library(RASbound)

x0 <- matrix(c(2, 4, 6, 8), nrow = 2)
upper <- matrix(c(Inf, Inf, 12, Inf), nrow = 2)  # cap cell [1, 2] at 12

fit <- bras_freeze_hybrid(x0, row_targets = c(20, 20),
                          col_targets = c(15, 25), upper = upper)
fit
fit$matrix

Documentation

vignette("RASbound-intro"): introduction and choice of function.
vignette("RASbound-example"): a worked example with a real input-output-style table.
vignette("RASbound-diagnostics"): reading the results and diagnosing failures.

License

GPL-3. See LICENSE.md.