simIReff: Stochastic Simulation for Information Retrieval Evaluation: Effectiveness Scores

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

Documentation:

Reference manual: simIReff.pdf

Downloads:

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

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