Generates a six-panel plot of extinction risk metrics used in Population Viability Analysis (PVA). This is a function used by one of the vignettes in the MARSS-package.
A data matrix with 2 columns; time in first column and counts in second column. Note time is down rows, which is different than the base MARSS-package functions.
te
Length of forecast period (positive integer)
absolutethresh
Is extinction threshold an absolute number? (T/F)
threshold
Extinction threshold either as an absolute number, if absolutethresh=TRUE, or as a fraction of current population count, if absolutethresh=FALSE.
datalogged
Are the data already logged? (T/F)
silent
Suppress printed output? (T/F)
return.model
Return state-space model as marssMLE object? (T/F)
CI.method
Confidence interval method: "hessian", "parametrc", "innovations", or "none". See MARSSparamCIs.
CI.sim
Number of simulations for bootstrap confidence intervals (positive integer).
Details
Panel 1: Time-series plot of the data.
Panel 2: CDF of extinction risk.
Panel 3: PDF of time to reach threshold.
Panel 4: Probability of reaching different thresholds during forecast period.
Panel 5: Sample projections.
Panel 6: TMU plot (uncertainty as a function of the forecast).
Value
If return.model=TRUE, an object of class marssMLE.
Author(s)
Eli Holmes, NOAA, Seattle, USA.
eli(dot)holmes(at)noaa(dot)gov
References
Holmes, E. E., E. J. Ward, and M. D. Scheuerell (2012) Analysis of multivariate time-series using the MARSS package. NOAA Fisheries, Northwest Fisheries Science
Center, 2725 Montlake Blvd E., Seattle, WA 98112 Type RShowDoc("UserGuide",package="MARSS") to open a copy.
(theory behind the figure) Holmes, E. E., J. L. Sabo, S. V. Viscido, and W. F. Fagan. (2007) A statistical approach to quasi-extinction forecasting. Ecology Letters 10:1182-1198.
(CDF and PDF calculations) Dennis, B., P. L. Munholland, and J. M. Scott. (1991) Estimation of growth and extinction parameters for endangered species. Ecological Monographs 61:115-143.
(TMU figure) Ellner, S. P. and E. E. Holmes. (2008) Resolving the debate on when extinction risk is predictable. Ecology Letters 11:E1-E5.
See Also
MARSSbootmarssMLECSEGtmufigure
Examples
d = harborSeal[,1:2]
kem = CSEGriskfigure(d, datalogged = TRUE)
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(MARSS)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MARSS/CSEGriskfigure.Rd_%03d_medium.png", width=480, height=480)
> ### Name: CSEGriskfigure
> ### Title: Plot Extinction Risk Metrics
> ### Aliases: CSEGriskfigure
> ### Keywords: hplot
>
> ### ** Examples
>
> d = harborSeal[,1:2]
> kem = CSEGriskfigure(d, datalogged = TRUE)
Analysis assumes that data and threshold are already logged
Using an percentage threshold for the extinction threshold
Threshold is 90 percent decline
>
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> dev.off()
null device
1
>