sumplot | R Documentation |
A list of outputs from runEllipseSim
is summarised and optionally plotted.
simsum(simlist, component = c("fit","pred"), parm = "D", trueval = 4, compact = c("av.nCH", "nvalid", "RB", "RSE", "rRMSE", "COV"), dec = 3, maxfactor = 10) simplot(simlist, component = c("fit","pred"), parm = "D", trueval = 4, xval = 1:4, xlim = c(0.7, 4.3), ylim = c(-0.2, 0.2), legend = TRUE, pchi = c(21, 16, 22, 24), cexi = rep(1.2,4), ...)
simlist |
list, each component an output from runEllipseSim |
component |
character; from which set of output should parm be summarised? |
parm |
character name of parameter to summarise, default density |
trueval |
numeric true value of parm, default 4 animals / ha |
compact |
character vector for summary statistics to include in output (NULL for all) |
dec |
integer number of decimal places in output |
maxfactor |
numeric; extreme estimate filter (see Details) |
xval |
numeric vector of values |
xlim |
numeric limits of x-axis |
ylim |
numeric limits of y-axis |
legend |
logical; if TRUE a legend is displayed |
pchi |
numeric vector for symbol to use for each component of |
cexi |
numeric vector for symbol size to use for each component of |
... |
other arguments passed to |
For each replicate the input simlist has components “fit“ generated by extractfn and “pred“ generated by predict.secr. Argument ‘component’ chooses between these.
These functions meet the needs of Efford in prep. as shown in the package vignette, and may not be useful for novel applications.
Each component of simlist
should have the same number of components (ellipse scenarios).
Estimates with absolute value greater than maxfactor * trueval are set to NA (maxfactor is ignored if NULL).
The ... argument allows a few options such as "type = 'o'", but colour (bg) is set internally to white.
List of output matrices (tables) (returned invisibly by simplot
).
runEllipseSim
## Not run: nrepl <- 20 tr <- make.grid(6,6, spacing = 50, detector = 'proximity') simrandom <- vector('list') simrandomBVN <- vector('list') for (i in 1:4) { sigmaX <- 25/i^0.5; sigmaY <- 25*i^0.5 details <- list(distribution = 'binomial') ## uniform simrandom[[i]] <- runEllipseSim (nrepl, sigmaX, sigmaY, buffer = 200, ncores = 2, traps = tr, g0 = 0.2, D = 4, type = 'uniform', CL = TRUE, detectfn = 'HHN', details = details) ## bvn simrandomBVN[[i]] <- runEllipseSim (nrepl, sigmaX, sigmaY, buffer = 200, ncores = 2, traps = tr, lambda0 = 0.4, D = 4, type = 'BVN', CL = TRUE, detectfn = 'HHN', details = details) message ('Completed aspect ratio ', i) } simplot(list(Uniform = simrandom, BVN = simrandomBVN), legend = TRUE) simsum(list(Uniform = simrandom36.2, BVN = simrandomBVN36.2)) ## End(Not run)
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