opt_n_gof_bootstrapper: Bootstrap for Optimism and GoF
In SMAC-Group/simts: Time Series Analysis Tools

opt_n_gof_bootstrapper

R Documentation

Bootstrap for Optimism and GoF

Using the bootstrap approach, we simulate a model based on user supplied parameters, obtain the wavelet variance, and then V.

opt_n_gof_bootstrapper(
  theta,
  desc,
  objdesc,
  scales,
  model_type,
  N,
  robust,
  eff,
  alpha,
  H
)

`theta`	A `vector` with dimensions N x 1 that contains user-supplied initial values for parameters
`desc`	A `vector<string>` indicating the models that should be considered.
`objdesc`	A `field<vec>` that contains an object description (e.g. values) of the model.
`scales`	A `vec` containing the scales of the process.
`model_type`	A `string` containing the model type either: SSM or IMU
`N`	A `int` indicating how long the integer is.
`robust`	A `bool` indicating robust (T) or classical (F).
`eff`	A `double` that handles efficiency.
`H`	A `int` that indicates how many bootstraps should be obtained.