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r4ss (version 1.44.0)

SSplotRetroRecruits: Make squid plot of retrospectives of recruitment deviations.

Description

Inspired by Jim Ianelli and named by Sean Cox, the squid plot is a way to examine retrospective patterns in estimation of recruitment deviations.

Usage

SSplotRetroRecruits(
  retroSummary,
  endyrvec,
  cohorts,
  ylim = NULL,
  uncertainty = FALSE,
  labels = c("Recruitment deviation", "Recruitment (billions)",
    "relative to recent estimate", "Age"),
  main = "Retrospective analysis of recruitment deviations",
  mcmcVec = FALSE,
  devs = TRUE,
  relative = FALSE,
  labelyears = TRUE,
  legend = FALSE,
  leg.ncols = 4
)

Arguments

retroSummary

List object created by SSsummarize() that summarizes the results of a set of retrospective analysis models.ss

endyrvec

Vector of years representing the final year of values to show for each model.

cohorts

Which cohorts to show in plot.

ylim

Limits of y-axis.

uncertainty

Show uncertainty intervals around lines? (This can get a bit busy.)

labels

Vector of plot labels.

main

Title for plot.

mcmcVec

Either vector of TRUE/FALSE values indicating which models use MCMC. Or single value applied to all models.

devs

Plot deviations instead of absolute recruitment values?

relative

Show deviations relative to most recent estimate or relative to 0.

labelyears

Label cohorts with text at the end of each line?

legend

Add a legend showing which color goes with which line (as alternative to labelyears).

leg.ncols

Number of columns for the legend.

References

Ianelli et al. (2011) Assessment of the walleye pollock stock in the Eastern Bering Sea. (Figure 1.31, which is on an absolute, rather than log scale.)

See Also

SSsummarize()

Examples

Run this code
# NOT RUN {
# run retrospective analysis
SS_doRetro(olddir = "2013hake_12", years = 0:-10)
# read in output
retroModels <- SSgetoutput(dirvec = paste("retrospectives/retro", -10:0, sep = ""))
# summarize output
retroSummary <- SSsummarize(retroModels)

# set the ending year of each model in the set
endyrvec <- retroModels[[1]][["endyr"]] - 10:0
# make comparison plot
pdf("retrospectives/retrospective_comparison_plots.pdf")
SSplotComparisons(retroSummary, endyrvec = endyrvec, new = FALSE)
dev.off()

# make Squid Plot of recdev retrospectives
pdf("retrospectives/retrospective_dev_plots.pdf", width = 7, height = 10)
par(mfrow = c(2, 1))
# first scaled relative to most recent estimate
SSplotRetroRecruits(retroSummary,
  endyrvec = endyrvec, cohorts = 1999:2012,
  relative = TRUE, legend = FALSE
)
# second without scaling
SSplotRetroDevs(retroSummary,
  endyrvec = endyrvec, cohorts = 1999:2012,
  relative = FALSE, legend = FALSE
)
dev.off()
# }
# NOT RUN {
# }

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