Fit Multiple SECR Models
par.secr.fit (arglist, ncores = 1, seed = NULL, trace = TRUE, logfile = "logfile.txt",
prefix = "fit.", LB = FALSE, save.intermediate = FALSE)
par.derived (secrlist, ncores = 1, ...)
par.region.N (secrlist, ncores = 1, ...)arglist |
list of argument lists for |
ncores |
integer number of cores to be used for parallel processing |
seed |
integer pseudorandom number seed |
trace |
logical; if TRUE intermediate output may be logged |
logfile |
character name of file to log progress reports |
prefix |
character prefix for names of output |
LB |
logical; if TRUE then use load balancing |
save.intermediate |
logical; if TRUE then each fit is saved to an external file |
... |
other arguments passed to |
secrlist |
secrlist object |
From version 4.0, an arglist may specify ncores for a
particular secr fit (previously ncores was ignored in arglist).
trace overrides any settings in arglist. Reporting of
intermediate results is unreliable on Windows when ncores > 1.
It is convenient to provide the names of the capthist and mask arguments in each component of arglist as character values (i.e. in quotes); objects thus named are exported from the workspace to each worker process (see Examples).
Setting LB = TRUE when ncores > 1 causes the function to call clusterApplyLB instead of clusterApply. Load balancing in clusterApplyLB is likely to result in faster completion than the default if fits differ in their in execution time and ncores < length(arglist), but this cannot be guaranteed owing to the additional communication required with the worker processes. Results with LB = TRUE for a given seed may not be reproducible.
save.intermediate causes each fit to be saved to a file with extension .RData.
For par.derived - a list of dataframes output from
derived, applied to each model in turn.
For par.region.N - a list of dataframes output from
region.N, applied to each model in turn.
With the introduction of multi-threading in secr 4.0, par.secr.fit has lost its speed advantage.
## Not run:
fit0 <- list(capthist = 'captdata', model = g0~1)
fitb <- list(capthist = 'captdata', model = g0~b)
fits <- par.secr.fit (c('fit0','fitb'))
AIC(fits)
par.derived(fits, se.esa = FALSE)
par.region.N(fits)
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.