ricker: Ricker model with Poisson observations.
In pomp: Statistical Inference for Partially Observed Markov Processes

ricker is a pomp object encoding a stochastic Ricker model with Poisson measurement error.

The state process is N[t+1] = r N[t] exp(-N[t]+e[t]), where the e[t] are i.i.d. normal random deviates with zero mean and variance sigma^2. The observed variables y[t] are distributed as Poisson(phi N[t]).

pomp, gompertz, and the tutorials on the package website.

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pompExample(ricker)
plot(ricker)
coef(ricker)

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):
 ricker 
       r    sigma      phi        c      N_0      e.0 
44.70118  0.30000 10.00000  1.00000  7.00000  0.00000