library(mipfp)

# Define input data
sex <- c(Male = 23, Female = 27) # n. in each sex category
age <- c(Less18 = 16, Workage = 20, Senior = 14) # age bands
diploma <- c(Level1 = 20, Level2 = 18, Level3 = 6, Level4 = 6)

## Example with 2D (non-crosstabulated) constraints

# Define target
target <- list (sex, age, diploma)

# Make sure the algorithm knows to which constraint each target refers
descript <- list (1, 2, 3)

names <- list (names(sex), names(age), names(diploma))
weight_init <- array (1, c(2,3,4), dimnames = names)

# Those younger than 18 can't have advanced degrees
weight_init[, c("Less18"), c("Level3","Level4")] <- 0

result <- Ipfp(weight_init, descript, target, iter = 50,
               print = TRUE, tol = 1e-5)

result$x.hat # print the result

## Exmaple with 3D (crosstabulated) constraints

# Define the cross table
cross <- cbind(c(11,5,0,0), c(3,9,4,4), c(6,4,2,2))
rownames (cross) <- names (diploma)
colnames (cross) <- names(age)

# The target and descript have to be updated to include the cross table.
# Pay attention to the order of the arguments by declaring a contingency table.
# Then, we can execute the task and run Ipfp again:

# defining the new target and associated descript
target <- list(sex, age, diploma, cross)
descript <- list(1, 2, 3, c(3,2))

# running the Ipfp function
result <- Ipfp(weight_init, descript, target, iter = 50,
               print = TRUE, tol = 1e-5)

result$x.hat