Showing 7 of total 7 results (show query)
pik-piam
madrat:May All Data be Reproducible and Transparent (MADRaT) *
Provides a framework which should improve reproducibility and transparency in data processing. It provides functionality such as automatic meta data creation and management, rudimentary quality management, data caching, work-flow management and data aggregation. * The title is a wish not a promise. By no means we expect this package to deliver everything what is needed to achieve full reproducibility and transparency, but we believe that it supports efforts in this direction.
Maintained by Jan Philipp Dietrich. Last updated 10 days ago.
15 stars 11.03 score 83 scripts 38 dependents
tudo-r
BatchJobs:Batch Computing with R
Provides Map, Reduce and Filter variants to generate jobs on batch computing systems like PBS/Torque, LSF, SLURM and Sun Grid Engine. Multicore and SSH systems are also supported. For further details see the project web page.
Maintained by Bernd Bischl. Last updated 3 years ago.
85 stars 8.57 score 616 scripts 3 dependents
henrikbengtsson
R.rsp:Dynamic Generation of Scientific Reports
The RSP markup language makes any text-based document come alive. RSP provides a powerful markup for controlling the content and output of LaTeX, HTML, Markdown, AsciiDoc, Sweave and knitr documents (and more), e.g. 'Today's date is <%=Sys.Date()%>'. Contrary to many other literate programming languages, with RSP it is straightforward to loop over mixtures of code and text sections, e.g. in month-by-month summaries. RSP has also several preprocessing directives for incorporating static and dynamic contents of external files (local or online) among other things. Functions rstring() and rcat() make it easy to process RSP strings, rsource() sources an RSP file as it was an R script, while rfile() compiles it (even online) into its final output format, e.g. rfile('report.tex.rsp') generates 'report.pdf' and rfile('report.md.rsp') generates 'report.html'. RSP is ideal for self-contained scientific reports and R package vignettes. It's easy to use - if you know how to write an R script, you'll be up and running within minutes.
Maintained by Henrik Bengtsson. Last updated 1 years ago.
documentmarkupreportreproducibilityscience
31 stars 8.06 score 36 scripts 9 dependents
bnaras
distcomp:Computations over Distributed Data without Aggregation
Implementing algorithms and fitting models when sites (possibly remote) share computation summaries rather than actual data over HTTP with a master R process (using 'opencpu', for example). A stratified Cox model and a singular value decomposition are provided. The former makes direct use of code from the R 'survival' package. (That is, the underlying Cox model code is derived from that in the R 'survival' package.) Sites may provide data via several means: CSV files, Redcap API, etc. An extensible design allows for new methods to be added in the future and includes facilities for local prototyping and testing. Web applications are provided (via 'shiny') for the implemented methods to help in designing and deploying the computations.
Maintained by Balasubramanian Narasimhan. Last updated 9 months ago.
9 stars 5.33 score 47 scripts
eddelbuettel
prrd:Parallel Runs of Reverse Depends
Reverse depends for a given package are queued such that multiple workers can run the reverse-dependency tests in parallel.
Maintained by Dirk Eddelbuettel. Last updated 1 months ago.
hacktoberfestreverse-dependencies
12 stars 4.73 score 2 scriptseddelbuettel
RcppGetconf:'Rcpp' Interface for Querying System Configuration Variables
The 'getconf' command-line tool provided by 'libc' allows querying of a large number of system variables. This package provides similar functionality.
Maintained by Dirk Eddelbuettel. Last updated 3 months ago.
1 stars 3.54 score 2 scripts
cran
FreeSortR:Free Sorting Data Analysis
Provides tools for describing and analysing free sorting data. Main methods are computation of consensus partition and factorial analysis of the dissimilarity matrix between stimuli (using multidimensional scaling approach).
Maintained by Philippe Courcoux. Last updated 7 years ago.
1.00 score