diff --git a/articles/DataPrepare.html b/articles/DataPrepare.html index c24e2dbc..f4e54304 100644 --- a/articles/DataPrepare.html +++ b/articles/DataPrepare.html @@ -776,7 +776,7 @@
The script
argument is recognized by
NMstamp
, but you can add anything to this. We want to keep
descriptive note too. Another often useful piece of information is what
@@ -874,7 +874,7 @@
The best place to browse information about the package is here. The quickest way in is the Cheatsheet.
+The best place to browse information about the package is here. The quickest way in is the Cheatsheet.
- - + +NMdata
is on CRAN and MPN. To install from the package archive you are already using, do:
+install.packages("NMdata")
+library(NMdata)
See further below for instructions on how to install from other sources than your default archive, if need be.
On the data-generation side, functionality is provided for documentation of the datasets while generating them. Check out this vignette on the topic. There are functions for automatic checks of (some) data merges, handling and counting of exclusions flags, final preparations for ensuring readability in NONMEM, and ensuring traceability of datasets back to data generation scripts.
+On the data-generation side, functionality is provided for documentation of the datasets while generating them. Check out this vignette on the topic. There are functions for automatic checks of (some) data merges, handling and counting of exclusions flags, final preparations for ensuring readability in NONMEM, and ensuring traceability of datasets back to data generation scripts.
NMdataConf(as.fun="data.table")
res.dt <- NMscanData("xgxr001.lst",quiet=TRUE)
NMscanData
is very general, and should work with all kinds of models, and all kinds of other software and configurations. Take a look at this vignette for more info on the NONMEM data reader. Then you will learn how to access the meta data that will allow you to trace every step that was taken combining the data and the many checks that were done along the way too.
NMscanData
is very general, and should work with all kinds of models, and all kinds of other software and configurations. Take a look at this vignette for more info on the NONMEM data reader. Then you will learn how to access the meta data that will allow you to trace every step that was taken combining the data and the many checks that were done along the way too.
If you use the Github version, you may want to see the FAQ for how to install specific releases from Github (ensuring reproducibility).
+If you use the Github version, you may want to see the FAQ for how to install specific releases from Github (ensuring reproducibility).
The best way to report a bug or to request features is on github.
+The best way to report a bug or to request features is on github.
Please note that the patchwork project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
+Please note that the patchwork project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.