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Provides tools for the stochastic simulation of effectiveness scores to mitigate data-related limitations of Information Retrieval evaluation research, as described in Urbano and Nagler (2018) <doi:10.1145/3209978.3210043>. These tools include: fitting, selection and plotting distributions to model system effectiveness, transformation towards a prespecified expected value, proxy to fitting of copula models based on these distributions, and simulation of new evaluation data from these distributions and copula models.
Version: | 1.0 |
Depends: | R (≥ 3.4) |
Imports: | stats, graphics, MASS, rvinecopulib (≥ 0.2.8.1.0), truncnorm, bde, ks, np, extraDistr |
Published: | 2018-06-15 |
DOI: | 10.32614/CRAN.package.simIReff |
Author: | Julián Urbano [aut, cre], Thomas Nagler [ctb] |
Maintainer: | Julián Urbano <urbano.julian at gmail.com> |
BugReports: | https://github.com/julian-urbano/simIReff/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/julian-urbano/simIReff/ |
NeedsCompilation: | no |
CRAN checks: | simIReff results |
Reference manual: | simIReff.pdf |
Package source: | simIReff_1.0.tar.gz |
Windows binaries: | r-devel: simIReff_1.0.zip, r-release: simIReff_1.0.zip, r-oldrel: simIReff_1.0.zip |
macOS binaries: | r-release (arm64): simIReff_1.0.tgz, r-oldrel (arm64): simIReff_1.0.tgz, r-release (x86_64): simIReff_1.0.tgz, r-oldrel (x86_64): simIReff_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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