crawl (version 1.3-2)

crwSimulator: Construct a posterior simulation object for the CTCRW state vectors

Description

The crwSimulator 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

crwSimulator(object.crwFit, predTime = NULL, method =
  "IS", parIS = 1000, df = Inf, grid.eps = 1, crit = 2.5,
  scale = 1)

Arguments

object.crwFit

A model object from crwMLE.

predTime

vector of additional prediction times.

method

Method for obtaining weights for movement parameter samples

parIS

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

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
  Covaraince 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

Details

The crwSimulator function produces a list and preprocesses the necessary components for repeated track simulation from a fitted CTCRW model from crwMLE. The method argument can be one of "IS" or "quadrature". If method="IS" is chosen standard importance sampling will be used to calculate the appropriate weights via t proposal with df degrees of freedom. If df=Inf (default) then a multivariate normal distribution is used to approximate the parameter posterior. If method="quadrature", then a regular grid over the posterior is used to calculate the weights. The argument grid.eps controls the quadrature grid. The arguments are approximately the upper and lower limit in terms of standard deviations of the posterior. The default is grid.eps, in units of 1sd. If object.crwFit was fitted with crwArgoFilter, then the returned list will also include p.out, which is the approximate probability that the observation is an outlier.

See Also

See northernFurSeal for example.