tsprofile: Model Simulation Based Profiling

In tsmodels/tsvets: Vector ETS Models

Model Simulation Based Profiling

Description

Profiling of model dynamics using simulation/estimation/prediction.

Usage

## S3 method for class 'tsvets.estimate'
tsprofile(
  object,
  h = 1,
  nsim = 100,
  seed = NULL,
  trace = FALSE,
  solver = "nlminb",
  autodiff = FALSE,
  ...
)

Arguments

object	an object of class “tsvets.estimate”.
h	the forecast horizon on which to evaluate performance metrics.
nsim	the number of paths to generate.
seed	an object specifying if and how the random number generator should be initialized. See the simulate documentation for more details.
trace	whether to show the progress bar. The user is expected to have set up appropriate handlers for this using the “progressr” package.
solver	choice of solver to use for the estimation of the paths.
autodiff	whether to use automatic differentiation for estimation. This makes use of the tsvetsad package.
...	not currently used.

Details

The function profiles an estimated model by simulating and then estimating multiple paths from the assumed DGP while leaving h values out for prediction evaluation. Each simulated path is equal to the size of the original dataset plus h additional values, and initialized with the initial state vector from the model. A data.table matrix is returned with the distribution of the coefficients from each path estimation as well as a stats table with the MAPE, BIAS and MSLRE by horizon, simulation and series.

Value

An object of class “tsvets.profile”.

Note

The function can use parallel functionality as long as the user has set up a plan using the future package.

tsmodels/tsvets documentation built on June 13, 2022, 2:14 p.m.