spatPomp (version 0.36.1)

lorenz: Lorenz '96 spatPomp simulator

Description

Generate a spatPomp object representing a U-dimensional stochastic Lorenz '96 process with N measurements made at times \(t_n = n * delta_obs\), simulated using an Euler method with time increment delta_t.

Usage

lorenz(
  U = 5,
  N = 100,
  delta_t = 0.01,
  delta_obs = 0.5,
  regular_params = c(F = 8, sigma = 1, tau = 1)
)

Value

An object of class ‘spatPomp’ representing a simulation from a U-dimensional Lorenz 96 model

Arguments

U

A length-one numeric signifying the number of spatial units for the process.

N

A length-one numeric signifying the number of observations.

delta_t

A length-one numeric giving the Euler time step for the numerical solution.

delta_obs

A length-one numeric giving the time between observations.

regular_params

A named numeric vector containing the values of the F, sigma and tau parameters. F=8 is a common value that causes chaotic behavior.

Author

Edward L. Ionides

References

Lorenz, E. N. (1996) Predictability: A problem partly solved. Proceedings of the seminar on predictability

Ionides, E. L., Asfaw, K., Park, J., and King, A. A. (2021). Bagged filters for partially observed interacting systems. Journal of the American Statistical Association, tools:::Rd_expr_doi("10.1080/01621459.2021.1974867")

See Also

Other spatPomp model generators: bm(), bm2(), gbm(), he10(), measles()

Examples

# Complete examples are provided in the package tests
if (FALSE) {
l <- lorenz(U=5, N=100, delta_t=0.01, delta_obs=1)
# See all the model specifications of the object
spy(l)
}