ricker: Ricker model with Poisson observations.

In kidusasfaw/pomp: Statistical Inference for Partially Observed Markov Processes

Description

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

Usage

ricker(r = exp(3.8), sigma = 0.3, phi = 10, c = 1, N_0 = 7)

Arguments

r	intrinsic growth rate
sigma	environmental process noise s.d.
phi	sampling rate
c	density dependence parameter
N_0	initial condition

Details

The state process is N[t+1] = r N[t] exp(-c 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]).

Value

A ‘pomp’ object containing the Ricker model and simulated data.

See Also

Other pomp examples: blowflies, dacca, gompertz, measles, ou2, rw2, sir_models, verhulst

Examples

plot(ricker())
coef(ricker())
simulate(ricker())

kidusasfaw/pomp documentation built on May 20, 2019, 2:59 p.m.