Package: ESTER
Title: Efficient Sequential Testing with Evidence Ratios
Version: 0.1.0
Date: 2017-10-15
Authors@R: person("Ladislas", "Nalborczyk", email = "ladislas.nalborczyk@gmail.com",
  role = c("aut", "cre"))
Description: An implementation of sequential testing that uses evidence ratios
    computed from the Akaike weights of a set of models. These weights are
    being computed using either the Akaike Information Criterion (AIC) or the
    Bayesian Information Criterion (BIC), and following
    Burnham & Anderson (2004) recommendations.
    Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference:
    Understanding AIC and BIC in model selection.
    Sociological Methods and Research, 33(2), 261-304.
    <doi:10.1177/0049124104268644>.
License: MIT + file LICENSE
LazyData: yes
RoxygenNote: 6.0.1
Depends: R (>= 3.3.0)
Imports: lme4, dplyr, magrittr, ggplot2, rlang
URL: https://github.com/lnalborczyk/ESTER
BugReports: https://github.com/lnalborczyk/ESTER/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-10-16 14:02:07 UTC; Ladislas
Author: Ladislas Nalborczyk [aut, cre]
Maintainer: Ladislas Nalborczyk <ladislas.nalborczyk@gmail.com>
Repository: CRAN
Date/Publication: 2017-10-16 14:22:05 UTC
