lorenz {spatPomp}

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)
)

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.

Value

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

Author(s)

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, 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
## Not run: 
l <- lorenz(U=5, N=100, delta_t=0.01, delta_obs=1)
# See all the model specifications of the object
spy(l)

## End(Not run)