inst/examples/ricker.R

In pomp: Statistical Inference for Partially Observed Markov Processes

require(pomp)

dat <- '"time";"y"
0;68
1;2
2;87
3;0
4;12
5;174
6;0
7;0
8;1
9;57
10;11
11;178
12;0
13;1
14;0
15;34
16;72
17;3
18;101
19;0
20;8
21;156
22;0
23;0
24;3
25;93
26;0
27;17
28;121
29;0
30;0
31;19
32;107
33;0
34;4
35;127
36;0
37;1
38;47
39;8
40;117
41;0
42;3
43;82
44;2
45;39
46;70
47;11
48;275
49;0
50;0
'

pomp(
     data=read.csv2(text=dat),
     times="time",
     t0=0,
     params=c(r=exp(3.8),sigma=0.3,phi=10,N.0=7,e.0=0), # originally used to generate the data
     rprocess=discrete.time.sim(
       step.fun="_ricker_simulator"
       ),
     rmeasure="_ricker_poisson_rmeasure",
     dmeasure="_ricker_poisson_dmeasure",
     skeleton.type="map",
     skeleton="_ricker_skeleton",
     paramnames=c("r","sigma","phi"),
     statenames=c("N","e"),
     toEstimationScale=function(params,...) {
       params[c("r","sigma","phi","N.0")] <- log(params[c("r","sigma","phi","N.0")])
       params
     },
     fromEstimationScale=function(params,...) {
       params[c("r","sigma","phi","N.0")] <- exp(params[c("r","sigma","phi","N.0")])
       params
     },
     PACKAGE="pomp"
     ) -> ricker

c("ricker")