CompareMaxDev

0th

Percentile

Comparing deviations of mipfp objects

This function compares either the margins errors from different mipfp objects or the absolute maximum deviation between a given table and the estimates in the mipfp objects.

Keywords
univar
Usage
CompareMaxDev(list.mipfp = list(), true.table = NULL, echo = FALSE)
Arguments
list.mipfp

The list produced by the function Estimate.

true.table

When provided, the estimates contained in the mipfp objects in the list list.mipfp are compared against this table. It is an optional argument.

echo

Verbose parameter. If TRUE, the function prints what is being compared. Default is FALSE.

Value

A table with as many rows as the number of mipfp objects in list.mipfp. Each row details the margins errors or the maximum absolute deviation of one mipfp object.

See Also

The estimation function Estimate.

This function is used by error.margins.mipfp.

Aliases
  • CompareMaxDev
Examples
# NOT RUN {
# loading the data
data(spnamur, package = "mipfp")
# subsetting the data frame, keeping only the first 3 variables
spnamur.sub <- subset(spnamur, select = Household.type:Prof.status)
# true table
true.table <- table(spnamur.sub)
# extracting the margins
tgt.v1        <- apply(true.table, 1, sum)
tgt.v1.v2     <- apply(true.table, c(1,2), sum)
tgt.v2.v3     <- apply(true.table, c(2,3), sum)
tgt.list.dims <- list(1, c(1,2), c(2,3))
tgt.data      <- list(tgt.v1, tgt.v1.v2, tgt.v2.v3)
# creating the seed, a 10% sample of spnamur
seed.df <- spnamur.sub[sample(nrow(spnamur), round(0.10*nrow(spnamur))), ]
seed.table <- table(seed.df)
# applying the different fitting methods
r.ipfp <- Estimate(seed=seed.table, target.list=tgt.list.dims, 
                   target.data = tgt.data,  method = "ipfp")
r.ml   <- Estimate(seed = seed.table, target.list = tgt.list.dims, 
                   target.data = tgt.data, method = "ml")
r.chi2 <- Estimate(seed = seed.table, target.list = tgt.list.dims, 
                   target.data = tgt.data, method = "chi2")
r.lsq  <- Estimate(seed = seed.table, target.list = tgt.list.dims, 
                   target.data = tgt.data, method = "lsq")
# print the maximum absolute deviation between targets and generated margins
CompareMaxDev(list(r.ipfp,r.ml,r.chi2,r.lsq), echo = TRUE)
# compute the maximum absolute deviation between the true and estimated tables
CompareMaxDev(list(r.ipfp,r.ml,r.chi2,r.lsq), echo = TRUE, 
              true.table = true.table)
# }
Documentation reproduced from package mipfp, version 3.2.1, License: GPL-2

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