xbio {plotMCMC}

MCMC Results for Biomass

Description

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

Usage

xbio

Format

Data frame containing 1000 rows and 34 columns (years 1971 to 2004).

Details

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.

Note

Biomass is the total weight of all individuals in a population, in this case ages 4 and older.

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, xbio <- xmcmc$B.

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

References

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.

See Also

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.

Examples

plotDens(xbio$"2004", points=TRUE, div=1000, main="2004\n",
         xlab="Biomass age 4+ (1000 t)", tick.number=6, strip=FALSE)

plotQuant(xbio, div=1000, xlab="Year", ylab="Biomass age 4+ (kt)")
plotQuant(xbio, style="bars", div=1000, sfrac=0, xlab="Year",
          ylab="Biomass age 4+ (kt)")
plotQuant(xbio, style="lines", div=1000, xlab="Year",
          ylab="Biomass age 4+ (kt)")