Conditionally linear model from constant coefficients

Convenience constructor for a conditional-Gaussian system whose coupling and self-drift are constant, supplied either as scalars or as full coefficient matrices.

Usage

aci_linear_model(lambda_x, lambda_y, fx, fy, sigma_x, sigma_y, k = 1, l = 1)

Arguments

lambda_x

Coupling of the hidden state into the observed drift; a finite scalar or a k by l matrix.

lambda_y

Hidden self-drift; a finite scalar or an l by l matrix.

fx

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

fy

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

sigma_x

Observed noise amplitude.

sigma_y

Hidden noise amplitude.

k

Observed dimension; a positive whole number.

l

Hidden dimension; a positive whole number.

Value

An object of class cgns_model.

See also

aci_model()

Examples

aci_linear_model(
  lambda_x = 1, lambda_y = -0.5,
  fx = function(t, x) -0.5 * x, fy = 0,
  sigma_x = 0.5, sigma_y = 1)
#> <aci_linear_model> 'conditionally_linear': k = 1 observed, l = 1 hidden