.updateSSSystem: Updates the system matrices of an object of class `NAWRUmodel` or `TFPmodel` during optimization or during a Bayesian Gibbs procedure.

Description

Updates the system matrices of an object of class NAWRUmodel or TFPmodel during optimization or during a Bayesian Gibbs procedure.

.updateSSSystem(
  pars,
  SSModel,
  loc,
  cycle,
  trend,
  errorARMA,
  signalToNoise = NULL,
  type = NULL,
  bayes = FALSE
)

pars: A vector of parameters.
SSModel: An object of class SSModel specifying the state-space model.
loc: A data frame containing information on each involved parameter, for instance its corresponding system matrix, variable names, and parameter restrictions.
cycle: A character string specifying the cycle model. cycle = "AR1" denotes an AR(1) process, cycle = "AR2" an AR(2) process. The default is cycle = "AR2".
trend: A character string specifying the trend model. trend = "RW1" denotes a first order random walk, trend = "RW2" a second order random walk (local linear trend) and trend = "DT" a damped trend model. The default is trend = "RW2".
errorARMA: A vector with non-negative integers specifying the AR and MA degree of the error term in the second observation equation.
signalToNoise: (Optional) signal to noise ratio. Only used if method = "MLE".
type: A character string specifying the type of the Phillip's curve. type = "TKP" denotes the traditional Keynesian Phillip's curve and type = "NKP" the New Keynesian Phillip's curve, see details. The default is type = "TKP".
bayes: A logical indicating whether the update is part of a Bayesian procedure, i.e., the parameter constraints do not need to be enforced.