gmwm_update_cpp: Update Wrapper for the GMWM Estimator
In schoi355/gmwm: Generalized Method of Wavelet Moments

gmwm_update_cpp

R Documentation

Update Wrapper for the GMWM Estimator

Description

This function uses information obtained previously (e.g. WV covariance matrix) to re-estimate a different model parameterization

Usage

gmwm_update_cpp(theta, desc, objdesc, model_type, N, expect_diff, ranged,
  orgV, scales, wv, starting, compute_v, K, H, G, robust, eff)

Arguments

`theta`	A `vec` 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>` containing a list of parameters (e.g. AR(1) = c(1,1), ARMA(p,q) = c(p,q,1))
`model_type`	A `string` that represents the model transformation
`scales`	A `vec` that contains the scales or taus (2^(1:J))
`starting`	A `bool` that indicates whether we guessed starting (T) or the user supplied estimates (F).
`wv_empir`	A `vec` that contains the empirical wavelet variance
`omega`	A `mat` that represents the covariance matrix.

Value

A field<mat> that contains the parameter estimates from GMWM estimator.

Author(s)

JJB

References

Wavelet variance based estimation for composite stochastic processes, S. Guerrier and Robust Inference for Time Series Models: a Wavelet-Based Framework, S. Guerrier

schoi355/gmwm documentation built on April 11, 2022, 1:21 a.m.