blowSimul: Simulates from the blowfly model

In synlik: Synthetic Likelihood Methods for Intractable Likelihoods

Simulates from the blowfly model

Description

Simulator for the blowfly model proposed by Wood (2010).

Usage

blowSimul(param, nsim, extraArgs, ...)

Arguments

param	vector of log-parameters: delta, P, N0, var.p, tau and var.d. The interpretation of these parameters is described in Wood (2010).
nsim	Number of simulations from the model.
extraArgs	A named list of additional arguments: nObs = Length of each simulated time series. nBurn = Number of initial steps to be discarded before saving the following nObs steps. steps = Positive integer. If steps == n the observations correspond to n time steps.
...	Need for compatibility with synlik, but not used.

Value

A matrix nsim by nObs, where each row is a simulated path.

Author(s)

Simon Wood and Matteo Fasiolo <[e-mail]>.

References

Simon N Wood. Statistical inference for noisy nonlinear ecological dynamic systems. Nature, 466(7310):1102–1104, 2010.

Brillinger, D. R., J. Guckenheimer, P. Guttorp, and G. Oster. 1980. Empirical modelling of population time series data: the case of age and density dependent vital rates. Lectures on Mathematics in the Life Sciences13:65-90.

Nicholson, A. J. 1957. The self-adjustment of populations to change. Cold Spring Harbor Symposia on Quantitative Biology22:153-173.

See Also

blow_sl

Examples

tmp <- blowSimul(param = log( c( "delta" = 0.16, "P" = 6.5, "N0" = 400, 
                                 "var.p" = 0.1, "tau" = 14, "var.d" = 0.1)  ), 
                 nsim = 2, 
                 extraArgs = list("nObs" = 200, "nBurn" = 1000, "steps" = 2))
matplot(t(tmp), type = 'l', ylab = "Y", xlab = "Time")

synlik documentation built on March 7, 2023, 8:39 p.m.