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CGNS model from an affine-in-hidden drift pair

Source: R/aci-model.R
aci_model_from_affine.Rd

Recovers the conditional-Gaussian coefficients from drift functions written in terms of the full state, by exact affine differencing. The supplied functions are checked before they are replaced by the reconstructed representation, so a drift that is not affine in the hidden state is rejected rather than silently linearised.

Usage

aci_model_from_affine(
  f_full,
  g_full,
  Sx,
  Sy_hidden,
  k,
  l,
  name = NULL,
  Sx2 = NULL,
  Sy_shared = NULL,
  meta = list()
)

Arguments

f_full

Function of (t, x, y) giving the full observed drift.

g_full

Function of (t, x, y) giving the full hidden drift.

Sx

Function of (t, x) giving the observed diffusion on the first Wiener channel.

Sy_hidden

Function of (t, x) giving the hidden diffusion on its own Wiener channel.

k

Observed dimension; a positive whole number.

l

Hidden dimension; a positive whole number.

name

Optional 1-length character label for the model.

Sx2

Optional function of (t, x) giving the observed diffusion on the second Wiener channel.

Sy_shared

Optional function of (t, x) giving the hidden diffusion on the shared Wiener channel, which introduces correlated noise.

meta

Optional named list of metadata carried on the object.

Value

An object of class cgns_model.

See also

aci_model()

Examples

aci_model_from_affine(
  f_full = function(t, x, y) -0.5 * x + y,
  g_full = function(t, x, y) -0.5 * y,
  Sx = function(t, x) matrix(0.5, 1, 1),
  Sy_hidden = function(t, x) matrix(1, 1, 1),
  k = 1, l = 1)
#> <cgns_model> 'cgns_model': k = 1 observed, l = 1 hidden