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c++ code for rank-swapping
Would it be possible to implement a parameter, in which one defines variables from the data set that are neither risk, similar nor hierachy variables? The variables that are chosen to be in this "carry along" parameter should have no influence on the outcome of the algorithm, but should be swapped in the same manner as the risky housholds are.
For example: I am swapping income tax data, and I want the income as risk variable, the age as similar variable and the usual geography as the hierachy. Now I also want the postal adresses carried along in the swapping process.
As far as I can see as of now the implentation does not allow for that.
Thanks and Regards
Michel Reiffert
Is the version 0.2.0 of recordSwapping disponible in R? Otherwise, when will it be disponible?
In relation to multiple similarity profiles of version 0.2.0, what exactly it consists of? For example, when you say that the first similarity profile is hsize, htype and hincome, and the second similarity profile is the hsize, how it will proceed?
Thank you
Hello,
I don't understand why I am getting this error. Variable hid has the column index 40 and my data has 48 columns, could you help me? Thanks
Error in checkIndexString(hid, cnames, matchLength = 1) :
Columnname(s) in hid are not found in data
Dear alexkowa,
Does this package have a version of CRAN? Many thanks.
Best Wishes
Tang Zhiqiang
In my microdata the householdID is 12 digits (maximum).
When I apply record swapping, I get negative housholdIDs back.
Looks like householdID needs to be integer and thus any number > MAXINT (=2147483647) is mapped to a negative number? The maximum householdID I find in the output is exactly 2147483647.
Can this be changed to allow for larger number of digits?
Hello,
I'd like to try this method. The test data are running fine.
What I don't understand is, do we use individual data (eg. sex, age), or household data (eg. household size). It seems like it is combined somehow.
Do we have to have 4 geography level?
Does the data have to be grid-like?
Thank you for that!
Niki Pálmai (HCSO)
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