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)
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