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icesAdvice (version 2.1.1)

mohn: Mohn's Rho

Description

Calculate Mohn's rho, the average relative bias of retrospective estimates.

Usage

mohn(x, peels = 5, details = FALSE, plot = FALSE, ...)

Arguments

x

a matrix or data frame containing retrospective estimates in columns, with years as row names.

peels

the number of retrospective peels to use in the calculation of rho, or NULL to use all retrospective columns in x.

details

whether to return the intermediate calculations of relative bias.

plot

whether to plot the retrospective trajectories.

passed to matplot and points.

Value

Mohn's rho, along with intermediate calculations if details = TRUE.

Details

The default value peels = 5 is based on the ICES (2018) guidelines.

The basic plot = TRUE functionality is intended to quickly visualize the calculation of Mohn's rho. To produce a fully formatted plot, bypass the mohn function and plot the x data directly.

References

Brooks, E. N. and Legault, C. M. (2016) Retrospective forecasting --- evaluating performance of stock projections in New England groundfish stocks. Canadian Journal of Fisheries and Aquatic Sciences, 73, 935--950.

ICES (2018) Guidelines for calculating Mohn's rho: Retrospective bias in assessment. Draft document version 7 (2018-04-03), available at the Expert Groups area on the ICES Sharepoint.

ICES (2020) Workshop on Catch Forecast from Biased Assessments (WKFORBIAS; outputs from 2019 meeting). 10.17895/ices.pub.5997ICES Scientific Reports 2(28).

Mohn, R. (1999) The retrospective problem in sequential population analysis: An investigation using cod fishery and simulated data. ICES Journal of Marine Science, 56, 473--488.

See Also

shake is a retrospective example table.

icesAdvice-package gives an overview of the package.

Examples

Run this code
# NOT RUN {
mohn(shake)
mohn(shake, details=TRUE)
mohn(shake, plot=TRUE)

mohn(shake, peels=3, plot=TRUE, col="black", ylim=0:1, yaxs="i")
lines(as.numeric(rownames(shake)), shake$base, lwd=3)

## Plot last 10 years
x <- rbind(matrix(1,28,6,dimnames=list(1981:2008,names(shake))), shake)
mohn(tail(x, 10), plot=TRUE, lwd=2, main="main")

# }

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