Simulates from the blowfly model

Description

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

Usage

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  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 <matteo.fasiolo@gmail.com>.

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

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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")