assoc_data {exams.forge} | R Documentation |
Frequency Optimization
Description
Given a frequency table, the function reorders the observations such that the given target
association will be approximated and the marginal
frequencies remain unchanged. Note that the target
association may not be reached!
zero
allows for zero entries in the common distribution.
If target
is NA
then the table is simply returned. FUN
computes the association (or correlation) measure based on a
frequency table. tol
gives the maximal deviation of the association (or correlation) measure
and the target
value. maxit
limits the number of steps.
Please note that a solution is not guaranteed, especially for extreme values of target
, for example
for +1
, -1
or nearby values.
If attr(joint, "iterations")== maxit
then you need either to increase maxit
, to decrease tol
, or
check if you have chosen an appropriate target
value (for a nominal measure in 0 <= target <= 1
, for ordinal measure in -1 <= target <= +1
).
attr(joint, "target")
contains the achieved association.
Usage
assoc_data(
tab,
zero = FALSE,
FUN = nom.cc,
target = NA,
tol = 0.001,
maxit = 500,
...
)
reorder_association_data(
tab,
zero = FALSE,
FUN = nom.cc,
target = NA,
tol = 0.001,
maxit = 500,
...
)
dassoc(
tab,
zero = FALSE,
FUN = nom.cc,
target = NA,
tol = 0.001,
maxit = 500,
...
)
Arguments
tab |
table: table of absolute frequencies |
zero |
logical: zeros are allowed in the final probabilities (default: |
FUN |
function: association or correlation function (default: |
target |
numeric: target association or correlation (default: |
tol |
numeric: tolerance for target association or correlation (default: |
maxit |
integer: maximal number of iterations (default: |
... |
further parameters |
Value
a modified frequency table
Examples
tab <- table_data(3, 2)
tab
tab2 <- assoc_data(tab, target=0.5)
tab2