Metapopulation Simulations for Conserving Salmon Through
Portfolio Optimization
c(person(given = c("Sean", "C."),
family = "Anderson",
role = c("aut", "cre"),
email = "sean@seananderson.ca",
comment = c(ORCID = "0000-0001-9563-1937")),
person(c("Jonathan", "W."), "Moore", role = "ctb"),
person(c("Michelle", "M."), "McClure", role = "ctb"),
person(c("Nicholas", "K."), "Dulvy", role = "ctb"),
person(c("Andrew", "B."), "Cooper", role = "ctb"))
A tool to simulate salmon metapopulations and apply financial
portfolio optimization concepts. The package accompanies the paper
Anderson et al. (2015) <doi:10.1101/2022.03.24.485545>.
Sean C. Anderson [aut, cre] (<https://orcid.org/0000-0001-9563-1937>),
Jonathan W. Moore [ctb],
Michelle M. McClure [ctb],
Nicholas K. Dulvy [ctb],
Andrew B. Cooper [ctb]

The metafor package consists of a collection of functions
for conducting meta-analyses in R. Fixed- and random-effects
models (with and without moderators) can be fitted via the
general linear (mixed-effects) model. For 2x2 table data, the
Mantel-Hanszel and Peto's method are also implemented.

The metafor package consists of a collection of functions
for conducting meta-analyses in R. Fixed- and random-effects
models (with and without moderators) can be fitted via the
general linear (mixed-effects) model. For 2x2 table data, the
Mantel-Haenszel and Peto's method are also implemented.

The metafor package consists of a collection of functions
for conducting meta-analyses in R. The package includes
functions to calculate various effect size or outcome measures,
fit fixed-, random-, and mixed-effects models to such data,
carry out moderator and meta-regression analyses, and create
various types of meta-analytical plots. For meta-analyses of
2x2 table data, the Mantel-Haenszel and Peto's method are also
implemented.
2010-12-15 16:04:19 UTC; Wolfgang Viechtbauer

The metafor package consists of a collection of functions
for conducting meta-analyses in R. The package includes
functions to calculate various effect size or outcome measures,
fit fixed-, random-, and mixed-effects models to such data,
carry out moderator and meta-regression analyses, and create
various types of meta-analytical plots (e.g., forest, funnel,
radial, and L'Abbe plots). For meta-analyses of 2x2 table data,
the Mantel-Haenszel and Peto's method are also implemented.
2011-04-12 16:53:47 UTC; Wolfgang Viechtbauer