Description Usage Arguments Details Value Author(s) References
StateSpace will search the internal AKaerial index estimates and run a generic state space model over the range selected
1 2 3 4 5 6 7 8 9 10 11 12 13 | StateSpace(
area,
index,
years,
species,
N1 = c(1000, 1e+05),
r = c(-0.3, 0.3),
sigma = c(0, 0.3),
n.chains = 3,
n.thin = 1,
n.iter = 5000,
n.burnin = 1000
)
|
area |
The area code for dedicated MBM Alaska region surveys. Either folder.path or area must be specified. Acceptable values include:
|
index |
The index used. Acceptable values include:
|
years |
- The years to run the model over |
species |
- The accepted |
N1 |
- Initial population size in the format c(min, max) to establish log-scale uniformly-distributed prior |
r |
- Range of growth rate parameter in the format c(min, max) to establish normally-distributed prior |
sigma |
- Range of the process standard deviation parameter in the format c(min, max) to establish uniformly-distributed prior |
n.chains |
- Number of Monte Carlo chains |
n.thin |
- Model thin rate |
n.iter |
- Model iterations |
n.burnin |
- Burn-in iteration length |
A state-space model is a general term that usually refers to a model containing the true underlying (and unobserved) time-dependent state of the system and imperfect time-dependent observations. The states change with time so that the state at time t depends on the state at time t-1 (and potentially other factors). Here, the state is defined as the unobserved total population of geese or ducks in the survey area, and observations depend just on the state. A formal description is contained in GenericStateSpaceModel.Rmd, which is provided as the output to this function
Will generate an .html report to the current working directory
Charles Frost, charles_frost@fws.gov
Erik Osnas, erik_osnas@fws.gov
https://github.com/cfrost3/AKaerial
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