crwSamplePar: Create a weighted importance sample for posterior predictive track simulation.

Description

The crwSamplePar function uses a fitted model object from crwMLE and a set of prediction times to construct a list from which crwPostIS will draw a sample from either the posterior distribution of the state vectors conditional on fitted parameters or a full posterior draw from an importance sample of the parameters.

Usage

crwSamplePar(
  object.sim,
  method = "IS",
  size = 1000,
  df = Inf,
  grid.eps = 1,
  crit = 2.5,
  scale = 1,
  quad.ask = T,
  force.quad
)

Value

List with the following elements:

x: Longitude coordinate with NA at prediction times
y: Similar to above for latitude
locType: Indicates prediction types with a "p" or observation times with an "o"
P1.y: Initial state covariance for latitude
P1.x: Initial state covariance for longitude
a1.y: Initial latitude state
a1.x: Initial longitude state
n.errX: number of longitude error model parameters
n.errY: number of latitude error model parameters
delta: vector of time differences
driftMod: Logical. indicates random drift model
stopMod: Logical. Indicated stop model fitted
stop.mf: stop model design matrix
err.mfX: Longitude error model design matrix
err.mfY: Latitude error model design matrix
mov.mf: Movement model design matrix
fixPar: Fixed values for parameters in model fitting
Cmat: Covariance matrix for parameter sampling distribution
Lmat: Cholesky decomposition of Cmat
par: fitted parameter values
N: Total number of locations
loglik: log likelihood of the fitted model
Time: vector of observation times
coord: names of coordinate vectors in original data
Time.name: Name of the observation times vector in the original data
thetaSampList: A list containing a data frame of parameter vectors and their associated probabilities for a resample

Arguments

object.sim: A simulation object from crwSimulator.
method: Method for obtaining weights for movement parameter samples
size: Size of the parameter importance sample
df: Degrees of freedom for the t approximation to the parameter posterior
grid.eps: Grid size for method="quadrature"
crit: Criterion for deciding "significance" of quadrature points (difference in log-likelihood)
scale: Scale multiplier for the covariance matrix of the t approximation
quad.ask: Logical, for method='quadrature'. Whether or not the sampler should ask if quadrature sampling should take place. It is used to stop the sampling if the number of likelihood evaluations would be extreme.
force.quad: A logical indicating whether or not to force the execution of the quadrature method for large parameter vectors.

Author

Devin S. Johnson

Details