pomp (version 0.53-5)

spect: Power spectrum computation for partially-observed Markov processes.

Description

spect estimates the power spectrum of time series data and model simulations and compares the results. It can be used to diagnose goodness of fit and/or as the basis for frequency-domain parameter estimation (spect.match).

spect.match tries to match the power spectrum of the model to that of the data. It calls an optimizer to adjust model parameters to minimize the discrepancy between simulated and actual data.

Usage

## S3 method for class 'pomp':
spect(object, params, vars, kernel.width, nsim, seed = NULL,
      transform = identity,
      detrend = c("none","mean","linear","quadratic"),
      ...)
  ## S3 method for class 'spect.pomp':
spect(object, params, vars, kernel.width, nsim, seed = NULL, transform,
      detrend, \dots)
  spect.match(object, start, est = character(0),
              vars, nsim, seed = NULL,
              kernel.width, transform = identity, 
              detrend = c("none","mean","linear","quadratic"),
              weights, method = c("subplex","Nelder-Mead","SANN"),
              verbose = getOption("verbose"),
              eval.only = FALSE, fail.value = NA, ...)

Value

• spect returns an object of class spect.pomp, which is derived from class pomp and therefore has all the slots of that class. In addition, spect.pomp objects have the following slots: [object Object],[object Object],[object Object],[object Object],[object Object],[object Object] spect.match returns an object of class spect.matched.pomp, which is derived from class {spect.pomp} and therefore has all the slots of that class. In addition, spect.matched.pomp objects have the following slots: [object Object],[object Object],[object Object],[object Object]

Details

A call to spect results in the estimation of the power spectrum for the (transformed, detrended) data and nsim model simulations. The results of these computations are stored in an object of class spect.pomp.

A call to spect.match results in an attempt to optimize the agreement between model and data spectrum over the parameters named in est. The results, including coefficients of the fitted model and power spectra of fitted model and data, are stored in an object of class spect.matched.pomp.

References

D.C. Reuman, R.A. Desharnais, R.F. Costantino, O. Ahmad, J.E. Cohen (2006) Power spectra reveal the influence of stochasticity on nonlinear population dynamics. Proceedings of the National Academy of Sciences 103, 18860-18865. D.C. Reuman, R.F. Costantino, R.A. Desharnais, J.E. Cohen (2008) Color of environmental noise affects the nonlinear dynamics of cycling, stage-structured populations. Ecology Letters, 11, 820-830.

See Also

pomp-class, pomp-methods, probe, probe.match

Examples

pompExample(ou2)
good <- spect(
              ou2,
              vars=c("y1","y2"),
              kernel.width=3,
              detrend="mean",
              nsim=500
              )
summary(good)
plot(good)

ou2.bad <- ou2
coef(ou2.bad,c("x1.0","x2.0","alpha.1","alpha.4")) <- c(0,0,0.1,0.2)
bad <- spect(
             ou2.bad,
             vars=c("y1","y2"),
             kernel.width=3,
             detrend="mean",
             nsim=500
             )
summary(bad)
plot(bad)