Description Usage Format Details Note References See Also Examples

Markov chain Monte Carlo results from stock assessment of cod
(*Gadus morhua*) in Icelandic waters, showing estimated
recruitment by year.

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Data frame containing 1000 rows and 33 columns (years 1970 to 2002).

Each column contains the results of 1 million MCMC iterations, after thinning to every 1000th iteration.

The MCMC analysis started at the best fit, so no burn-in period was discarded.

Recruitment is the size of a cohort (year class), in this case thousands of one-year-olds.

For example, `xrec$"1980"`

is the estimated number of
one-year-olds in 1981, the cohort that hatched in 1980.

This data frame is a subset of the `xmcmc`

list
from the scape package, which contains further documentation
about the data and model. More specifically, `xrec <- xmcmc$R`

.

The MCMC analysis was run using the AD Model Builder software (http://www.admb-project.org/).

Fournier, D. A., Skaug, H. J., Ancheta, J., Ianelli, J., Magnusson,
A., Maunder, M. N., Nielsen, A. and Sibert, J. (2012) AD Model
Builder: using automatic differentiation for statistical inference of
highly parameterized complex nonlinear models. *Optimization
Methods and Software*, **27**, 233–249.

Magnusson, A., Punt, A. E. and Hilborn, R. (2013) Measuring
uncertainty in fisheries stock assessment: the delta method,
bootstrap, and MCMC. *Fish and Fisheries*, **14**, 325–342.

`xpar`

(parameters), `xrec`

(recruitment),
`xbio`

(biomass), and `xpro`

(projected future
biomass) are MCMC data frames to explore.

`plotMCMC-package`

gives an overview of the package.

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