MARSS (version 3.2)

MARSShessian: MARSS Parameter Variance-Covariance Matrix from the Hessian Matrix

Description

Calculates approximate parameter variance-covariance matrix and appends it to a marssMLE object. This is a utility function in the MARSS-package.

Usage

MARSShessian(MLEobj, fun="MARSSkf")

Arguments

MLEobj

An object of class marssMLE. This object must have a $par element containing MLE parameter estimates from e.g. MARSSkem.

fun

The function to use to compute the log-likelihood.

Value

• MARSShessian() returns the marssMLE object passed in along with additional components Hessian, gradient, parMean and parSigma computed by the MARSShessian function.

Details

Uses fdHess from package nlme to numerically estimate the Hessian matrix (the matrix of partial 2nd derivatives of the parameter estimates). Hessian CIs are based on the asymptotic normality of ML estimates under a large-sample approximation.

See Also

MARSSparamCIs marssMLE

Examples

dat = t(harborSeal)
  dat = dat[c(2,11),]
  MLEobj = MARSS(dat)
  #show the approx Hessian
  MARSShessian(MLEobj)$Hessian