View source: R/moment-estimation.R
| smm_estimate | R Documentation |
Estimates structural parameters by minimising the distance between
simulated and empirical moments. Use when analytic model moments
are intractable (e.g. perturbed nonlinear models). For linear DSGEs
produced by solve_dsge, SMM and GMM give the same
large-sample point estimates but SMM is noisier; prefer
gmm_estimate unless you have a specific reason to
simulate.
smm_estimate(
model,
data,
moments,
params_start,
shock_sd_start,
weight = NULL,
lower = NULL,
upper = NULL,
method = "Nelder-Mead",
control = list(),
sim_periods = 1000L,
sim_replic = 5L,
seed = NULL
)
model |
A |
data |
Matrix or data frame of observed variables; column names must match a subset of the model's observables. |
moments |
Character vector naming the moments to match. Each
element uses the same naming convention as
|
params_start |
Named numeric vector of starting values for the structural parameters. |
shock_sd_start |
Named numeric vector of starting values for shock standard deviations. |
weight |
Optional positive-definite weighting matrix. Default
identity (one-step GMM). Pass |
lower, upper |
Bounds ( |
method |
Optimiser method for |
control |
|
sim_periods |
Integer. Length of each simulated path used to compute model moments. Default 1000. |
sim_replic |
Integer. Number of independent simulations averaged into the moment estimates. Default 5. |
seed |
Optional integer seed for reproducible simulations. |
An object of class c("dsge_smm","dsge_gmm").
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