R Dataset / Package Ecdat / USclassifiedDocuments
Documentation |
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On this R-data 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. You can load the USclassifiedDocuments data set in R by issuing the following command at the console data("USclassifiedDocuments"). This will 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. 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 GovernmentDescriptionData on classification activity of the United States government. Fitzpatrick (2013) notes that the dramatic jump in derivative classification activity ( Usagedata(USclassifiedDocuments) FormatA dataframe containing :
DetailsThe lag 1 autocorrrelation of the first difference of the logarithms of SourceFitzpatrick, 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) Examples## ## 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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Attachment | Size |
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dataset-90051.csv | 823 bytes |