R Dataset / Package Ecdat / USclassifiedDocuments
On this Picostat.com statistics page, you will find information about the USclassifiedDocuments data set which pertains to Official Secrecy of the United States Government . The USclassifiedDocuments data set is found in the Ecdat R package. Try to load the USclassifiedDocuments data set in R by issuing the following command at the console data("USclassifiedDocuments"). This may load the data into a variable called USclassifiedDocuments. If R says the USclassifiedDocuments data set is not found, you can try installing the package by issuing this command install.packages("Ecdat") and then attempt to reload the data with library("Ecdat") followed by data("USclassifiedDocuments"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing USclassifiedDocuments at the command-line which should display the entire dataset.
If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the USclassifiedDocuments R data set. The size of this file is about 823 bytes.
Official Secrecy of the United States Government
Data on classification activity of the United States government.
Fitzpatrick (2013) notes that the dramatic jump in derivative classification activity (
A dataframe containing :
The lag 1 autocorrrelation of the first difference of the
Fitzpatrick, John P. (2013) Annual Report to the President for 2012, United States Information Security Oversight Office, National Archives and Record Administration, June 20, 2013 (https://www.archives.gov/isoo/reports)
## ## 1. plot DerivClassActivity ## plot(DerivClassActivity~year, USclassifiedDocuments) # Exponential growth? plot(DerivClassActivity~year, USclassifiedDocuments, log='y') # A jump in 2009 as discussed by Fitzpatrick (2013). # Otherwise plausibly a straight line. ## ## 2. First difference? ## plot(diff(log(DerivClassActivity))~year[-1], USclassifiedDocuments) # Jump in 2009 but otherwise on distribution ## ## 3. autocorrelation? ## sel <- with(USclassifiedDocuments, (1995 < year) & (year < 2009) ) acf(diff(log(USclassifiedDocuments$ DerivClassActivity[sel]))) # lag 1 autocorrelation = (-0.52). # However, with only 12 numbers, # this is not statistically significant.
Dataset imported from https://www.r-project.org.
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