Rank Conditional Coverage Simulations

Last updated: 2018-04-25

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Welcome to the rank conditional coverage wimulations and examples website! Here you will find walkthroughs of all the simulations presented in the paper and some useful tips for running the package. The R package rcc can be installed from CRAN using

install.packages("rcc")

To run the simuations, we use a package rccSims that we wrote especially for this purpose. It can be installed using

devtools::install_git("https://github.com/jean997/rccSims.git")

sessionInfo()

R version 3.4.2 (2017-09-28)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 17.10

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.7.1
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.7.1

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
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[10] stringi_1.1.7     whisker_0.3-2     R.oo_1.21.0      
[13] R.utils_2.6.0     rmarkdown_1.9     tools_3.4.2      
[16] stringr_1.3.0     yaml_2.1.18       compiler_3.4.2   
[19] htmltools_0.3.6   knitr_1.20       

This reproducible R Markdown analysis was created with workflowr 1.0.1