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 |
| 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: simIReff_1.0.tgz, r-oldrel: simIReff_1.0.tgz |
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