gompertz: Gompertz model with log-normal observations.

In pomp: Statistical Inference for Partially Observed Markov Processes

Description

gompertz is a pomp object encoding a stochastic Gompertz population model with log-normal measurement error.

Details

The state process is X[t+1]=K^(1-S) X[t]^S eps[t], where S=e^{-r} and the eps[t] are i.i.d. lognormal random deviates with variance sigma^2. The observed variables Y_t are distributed as lognormal(log(X[t]),tau). Parameters include the per-capita growth rate r, the carrying capacity K, the process noise s.d. sigma, the measurement error s.d. tau, and the initial condition X[0]. The pomp object includes parameter transformations that log-transform the parameters for estimation purposes.

See Also

pomp, ricker, and the tutorials at http://pomp.r-forge.r-project.org.

Examples

pompExample(gompertz)
plot(gompertz)
coef(gompertz)
coef(gompertz,transform=TRUE)

Example output

Welcome to pomp version 1.19!
pomp version 2 is now available on https://kingaa.github.io/pomp/.
This new version contains many improvements but is not backward compatible.
To allow users time to modify their codes, 'pomp' version 2 will be provided as package 'pomp2' for a short while.

Around the middle of 2019, 'pomp2' will be renamed 'pomp' version 2.1 and will be released to CRAN. Until then, 'pomp' versions < 2 will continue to be available.

See the 'pomp version 2 upgrade guide' at https://kingaa.github.io/pomp/.
newly created object(s):
 gompertz 
    K     r sigma   tau   X.0 
  1.0   0.1   0.1   0.1   1.0 
        K         r     sigma       tau       X.0 
 0.000000 -2.302585 -2.302585 -2.302585  0.000000 

pomp documentation built on May 2, 2019, 4:09 p.m.