Stochastic Augmentation of Matched Data Using Restriction
Methods
Augmenting a matched data set by generating multiple stochastic, matched samples from the data using a
multi-dimensional histogram constructed from dropping the input matched data into a multi-dimensional grid built on
the full data set. The resulting stochastic, matched sets will likely provide a collectively higher coverage of the full
data set compared to the single matched set. Each stochastic match is without duplication, thus allowing downstream
validation techniques such as cross-validation to be applied to each set without concern for overfitting.

Sensitivity Analysis of a Meta-analysis with Unpublished but
Registered Analytical Investigations
Programmed by Noory Kim, with advising by Shrikant Bangdiwala
and Gerald Gartlehner. Thanks to Guido Schwartzer for
peer-reviewing the code. Sponsored by UNCOVER.
This package contains R functions to gauge the impact of
unpublished studies upon the meta-analytic summary effect of a
set of published studies.

Noory Y. Kim. Advisors: Shrikant I. Bangdiwala, Gerald
Gartlehner.
This package contains R functions to gauge the impact of
unpublished studies upon the meta-analytic summary effect of a
set of published studies. (Credits: The research leading to
these results has received funding from the European Union's
Seventh Framework Programme (FP7/2007-2013) under grant
agreement no. 282574.)

Noory Y. Kim. Advisors: Shrikant I. Bangdiwala, Gerald Gartlehner.
This package contains R functions to gauge the impact of unpublished studies upon the meta-analytic summary effect of a set of published studies. (Credits: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 282574.)

c(person("Quang", "Huynh", email = "quang@bluematterscience.com", role = c("aut", "cre")),
person("Tom", "Carruthers", email = "tom@bluematterscience.com", role = "aut"),
person("Adrian", "Hordyk", email = "adrian@bluematterscience.com", role = "aut"))
Simulation tools for closed-loop simulation are provided for the 'MSEtool' operating model to inform data-rich fisheries.
'SAMtool' provides a conditioning model, assessment models of varying complexity with standardized reporting,
model-based management procedures, and diagnostic tools for evaluating assessments inside closed-loop simulation.
TMB, corpcor, dplyr, gplots, grDevices, graphics, methods,
snowfall, stats, utils, rmarkdown
knitr, testthat, shiny, mvtnorm, reshape2
Quang Huynh [aut, cre],
Tom Carruthers [aut],
Adrian Hordyk [aut]