StateSpace | R Documentation |
StateSpace will search the internal AKaerial index estimates and run a generic state space model over the range selected
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,
output = "object"
)
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.
The current index objects in the package are ACPHistoric, CRDHistoric, YKDHistoric, and YKGHistoric.
Will generate an .html report to the current working directory
Charles Frost, charles_frost@fws.gov
Erik Osnas, erik_osnas@fws.gov
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