[R-sig-eco] zero-truncated Poisson
Stratford, Jeffrey
jeffrey.stratford at wilkes.edu
Sat Apr 9 02:40:35 CEST 2011
Thanks Ben,
That didn't do the trick. I checked all the classes
year size distance taken mass
"factor" "factor" "numeric" "integer" "numeric"
And used the notation that you suggested and I did get the same error.
Just so it's not such a black box for me, what makes vector GLMs
different from "ordinary" GLMs?
Thanks,
Jeff
Here's all the data.
structure(list(year = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label =
c("one",
"two"), class = "factor"), size = structure(c(2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L), .Label = c("large", "small"), class = "factor"), distance =
c(30.8735,
121.505, 46.055, 46.055, 46.055, 9.343, 46.055, 46.055, 46.055,
85.271, 85.271, 85.271, 85.271, 85.271, 85.271, 30.8735, 30.8735,
9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 152.717, 152.717,
152.717, 152.717, 152.717, 152.717, 152.717, 46.055, 46.055,
152.717, 152.717, 20.698, 20.698, 17.217, 17.217, 9.343, 9.343,
17.217, 46.055, 152.717, 46.055, 17.217, 152.717, 17.217, 17.217,
46.055, 30.8735, 30.8735, 30.8735, 5.69, 30.8735, 17.217, 30.8735,
30.8735, 30.8735, 30.8735, 30.8735, 9.343, 9.343, 17.217, 17.217,
17.217, 17.217, 17.217, 17.217, 9.343, 9.343, 17.217, 17.217,
17.217, 20.698, 17.217, 17.217, 17.217, 5.42, 17.217, 17.217,
17.217, 9.343, 30.8735, 30.8735, 30.8735, 9.343, 9.343, 9.343,
9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343,
17.217, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343,
30.8735, 30.8735, 17.217, 17.217, 46.055, 36.239, 17.217, 17.217,
17.217, 46.055, 30.8735, 30.8735, 17.217, 17.217, 17.217, 121.505,
152.717, 152.717, 17.217, 152.717, 121.505, 121.505, 121.505,
121.505, 121.505, 9.343, 121.505, 9.343, 121.505, 121.505, 30.8735,
121.505, 17.217, 17.217, 17.217, 9.343, 30.8735, 85.271, 85.271,
85.271, 85.271, 85.271, 85.271, 9.343, 85.271, 85.271, 85.271,
85.271, 20.698, 9.343, 30.8735, 17.217, 20.698, 30.8735, 17.217,
85.271, 121.505, 121.505, 85.271, 85.271, 85.271, 85.271, 121.505,
121.505, NA, 121.505, 9.343, 9.343, 9.343, 9.343, 9.343, 9.343,
9.343, 30.8735, 17.217, 9.343, 9.343, 9.343, 30.8735, 30.8735,
30.8735, 9.343, 9.343, 30.8735, 17.217, 5.42, 17.217, 85.271,
85.271, 30.8735, 30.8735, 30.8735, 30.8735, 30.8735, 30.8735,
17.217, 85.271, 17.217, 30.8735, 30.8735, 85.271, 30.8735, 30.8735,
85.271, 30.8735, 30.8735, 30.8735, 30.8735, 30.8735, 30.8735,
17.217, 30.8735, 9.343, 30.8735, 30.8735, 30.8735, 30.8735, 9.343,
30.8735, 30.8735, 17.217, 9.343, 9.343, 9.343, 85.271, 30.8735,
30.8735, 46.055, 5.69, 85.271, 85.271, 17.217, 46.055, 85.271,
30.8735, 85.271, 46.055, 121.505, 121.505, 121.505, 17.217, 17.217,
25.508, 9.343, 17.217, 17.217, 9.343, 17.217, 9.343, 17.217,
34.35, 34.35, 46.055, 46.055, 9.343, 20.698, 17.217, 27.25, 20.54,
27.25, 20.698, 17.217, 20.698, 20.698, 15, 15, 8.35, 13.63, 20.34,
17.217, 5.69, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 7.5, 30,
17.217, 5, 5, 5, 7.93, 7.93, 7.93, 5, 7.71, 5, 17.217, 8.175,
8.175, 6.69, 6.69, 6.69, 10.875, 5.345, 5.345, 5.345, 5.345,
3.54, 10.755, 10.755, 10.755, 19.61, 20.145, 20.145, 20.145,
10.34, 5.35, 6.34, 10.34, 5.35, 10.34, 9.343, 9.343, 9.343, 9.343,
137.111, 17.217, 137.111, 17.217, 137.111, 137.111, 17.217, 46.055,
46.055, 17.217, 17.77, 20.54, 17.217, 17.217, 20.54, 11.75, 11.75,
17.217, 56.89, 20.54, 20.54, 55, 75, 75, 75, 19.61, 19.61, 19.61,
19.61, 19.61, 25.508, 20.698, 5.42, 5.42, 19.61, 19.61, 19.61,
20.698, 5.42, 25.508, 5.42, 17.217, 16.92, 9.343, 9.343, 19.61,
9.343, 19.61, 19.61, 16.92, 16.92, 16.92, 5.42, 5.42, 19.61,
5.42, 9.343, 19.61, 5.42, 5.42, 19.61, 9.343, 46.055, 17.217,
5.42, 19.61, 5.69, 19.61, 17.217, 9.343, 5.42, 19.61, 19.61,
17.217, 35.508, 5.42, 5.42, 5.42, 19.61, 17.217, 5.69, 19.61,
19.61, 8.35, 17.217, 5.69, 19.61, 5.69, 5.69, 17.217, 19.61,
16.92, 19.61, 17.217, 9.343, 5.42, 17.217, 17.217, 9.343, 33.456,
17.217, 46.055, 137.11, 56.89, 54.25, 17.217, 56.89, 55, 17.217,
46.055, 20.698, 46.055, 54.25, 27.25, 53.5, 5.69, 53.5, 20.698,
20.698, 5.69, 17.217, 17.217, 17.217, 17.217, 17.217, 5.69, 17.217,
17.217, 17.217, 11.75, 17.217, 5.69, 11.75, 11.75, 5.42, 5.42,
17.217, 5.69, 20.54, 11.75, 5.69, 11.75, 17.217, 121.505, 121.505,
121.505, 11.75, 5.69, 11.75, 11.75, 20.698, 121.505, 17.217,
11.75, 17.217, 5.42, 17.217, 17.217, 5.42, 5.69, 121.505, 17.217,
5.42, 46.055, 5.69, 20.698, 46.055, 15.86, 15.86, 5.69, 5.69,
11.75, 5.42, 46.055, 5.42, 10.349, 121.505, 15.86, 25.508, 17.217,
17.217, 11.75, 17.217, 17.217, 17.217, 17.217, 17.217, 17.217,
46.055, 17.217, 17.217, 17.217, 17.217, 17.217, 5.42, 17.217,
17.217, 17.217, 9.343, 85.271, 46.055, 17.217, 17.217, 46.055,
25.508, 25.508, 25.508, 20.698, 19.61, 11.75, 11.75, 11.75, 20.698,
11.75, 11.75, 20.45, 11.75, 20.45, 20.45, 7.5, 11.75, 11.75,
20.45), taken = c(10L, 2L, 12L, 1L, 4L, 1L, 10L, 3L, 5L, 5L,
1L, 5L, 3L, 3L, 5L, 2L, 4L, 2L, 1L, 4L, 1L, 1L, 2L, 1L, 3L, 1L,
3L, 2L, 3L, 2L, 2L, 1L, 4L, 1L, 5L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
1L, 1L, 1L, 1L, 3L, 1L, 3L, 2L, 2L, 3L, 2L, 3L, 1L, 2L, 3L, 2L,
2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 1L,
4L, 2L, 3L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 1L, 2L, 3L, 1L, 1L, 1L, 3L, 1L, 1L, 1L, 1L, 1L, 3L, 4L, 2L,
1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 2L, 3L, 2L, 1L, 1L, 5L, 1L, 1L,
5L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 1L, 1L, 1L, 3L, 1L, 2L, 2L, 2L,
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L,
1L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L, 1L,
1L, 3L, 1L, 1L, 1L, 2L, 1L, 2L, 3L, 1L, 2L, 1L, 2L, 2L, 2L, 2L,
2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 2L, 1L, 2L, 2L, 2L, 1L, 3L, 2L,
2L, 3L, 3L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 3L, 2L, 4L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 3L, 3L, 2L, 2L, 4L,
1L, 2L, 4L, 3L, 3L, 4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 1L, 1L,
1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
3L, 2L, 2L, 2L, 3L, 3L, 2L, 2L, 2L, 3L, 2L, 2L, 2L, 2L, 2L, 2L,
3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 3L, 2L, 3L, 2L, 3L, 1L, 2L,
2L, 1L, 2L, 3L, 2L, 2L, 3L, 2L, 1L, 2L, 1L, 2L), mass = c(13.8758,
2.77516, 16.65096, 1.38758, 5.55032, 1.38758, 13.8758, 4.16274,
6.9379, 6.9379, 1.38758, 6.9379, 4.16274, 4.16274, 6.9379, 2.77516,
5.55032, 2.77516, 1.38758, 5.55032, 1.38758, 1.38758, 2.77516,
1.38758, 4.16274, 1.38758, 4.16274, 2.77516, 4.16274, 2.77516,
2.77516, 1.38758, 5.55032, 1.38758, 6.9379, 2.77516, 2.77516,
5.49268, 5.49268, 5.49268, 2.74634, 2.74634, 2.74634, 2.74634,
2.74634, 2.74634, 8.23902, 1.295, 3.885, 2.59, 2.59, 3.885, 2.59,
3.885, 1.295, 2.59, 3.885, 2.59, 2.59, 2.59, 1.295, 2.59, 2.59,
2.59, 1.295, 1.295, 1.295, 1.295, 1.295, 1.295, 2.59, 3.885,
2.59, 1.295, 5.18, 2.59, 3.885, 2.59, 1.295, 2.59, 1.295, 1.295,
1.295, 2.59, 2.59, 2.59, 2.59, 1.295, 2.59, 2.59, 2.59, 1.295,
2.59, 3.885, 1.295, 1.295, 1.295, 3.885, 1.295, 1.295, 1.295,
1.295, 1.295, 3.885, 5.18, 2.59, 1.295, 1.4429, 2.8858, 1.4429,
1.4429, 2.8858, 1.4429, 1.4429, 2.8858, 4.3287, 2.8858, 1.4429,
1.4429, 7.2145, 1.4429, 1.4429, 7.2145, 1.4429, 1.4429, 1.4429,
1.4429, 1.4429, 2.8858, 4.3287, 1.4429, 1.4429, 1.4429, 4.3287,
1.4429, 2.8858, 2.8858, 2.8858, 1.4429, 2.877, 2.877, 2.877,
2.877, 5.754, 2.877, 2.877, 2.877, 2.877, 2.877, 2.877, 8.631,
2.877, 2.877, 5.754, 2.877, 2.877, 2.877, 2.877, 5.754, 2.877,
2.877, 2.877, 2.877, 5.754, 5.754, 2.877, 2.877, 2.877, 2.877,
2.877, 2.877, 1.3719, 1.3719, 1.3719, 1.3719, 1.3719, 2.7438,
1.3719, 2.7438, 1.3719, 1.3719, 2.7438, 2.7438, 1.3719, 1.3719,
1.3719, 1.3719, 2.7438, 1.3719, 1.3719, 2.7438, 1.3719, 2.7438,
1.3719, 1.3719, 1.3719, 1.3719, 1.3719, 4.1157, 1.3719, 1.3719,
1.3719, 1.3719, 4.1157, 1.3719, 1.3719, 1.3719, 2.7438, 1.3719,
2.7438, 4.1157, 1.3719, 2.7438, 1.3719, 2.7438, 2.7438, 2.7438,
2.7438, 2.7438, 1.3719, 1.3719, 2.7438, 2.7438, 1.3719, 1.3719,
1.3719, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316,
2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316,
2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 2.8316, 1.17028, 2.34056,
1.17028, 1.17028, 1.17028, 1.17028, 1.17028, 1.17028, 2.34056,
2.34056, 3.51084, 2.34056, 1.17028, 2.34056, 2.34056, 2.34056,
1.17028, 3.51084, 2.34056, 2.34056, 3.51084, 3.51084, 2.34056,
1.17028, 2.03456, 4.06912, 2.03456, 2.03456, 2.03456, 4.06912,
2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456, 2.03456,
2.03456, 2.03456, 2.03456, 2.03456, 4.06912, 2.03456, 2.03456,
2.03456, 2.03456, 2.03456, 2.03456, 1.189102041, 1.189102041,
1.189102041, 2.378204082, 3.567306123, 2.378204082, 4.756408164,
2.378204082, 2.378204082, 2.378204082, 1.189102041, 1.189102041,
1.189102041, 1.189102041, 2.378204082, 1.189102041, 2.378204082,
1.189102041, 3.567306123, 3.567306123, 2.378204082, 2.378204082,
4.756408164, 1.189102041, 2.378204082, 4.756408164, 3.567306123,
3.567306123, 4.756408164, 2.45232, 2.45232, 2.45232, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
2.45232, 4.90464, 4.90464, 2.45232, 2.45232, 2.45232, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
7.35696, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 4.90464,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 4.90464, 2.45232,
2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232, 2.45232,
2.64516, 1.76344, 1.76344, 1.76344, 2.64516, 2.64516, 1.76344,
1.76344, 1.76344, 2.64516, 1.76344, 1.76344, 1.76344, 1.76344,
1.76344, 1.76344, 2.64516, 2.64516, 0.88172, 0.88172, 2.46532,
2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
2.46532, 2.46532, 4.93064, 2.46532, 2.46532, 2.46532, 2.46532,
2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
2.46532, 4.93064, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
4.93064, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532,
2.46532, 2.46532, 4.93064, 2.46532, 2.46532, 4.93064, 2.46532,
2.46532, 2.46532, 4.93064, 4.93064, 2.46532, 4.93064, 2.46532,
2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.46532, 2.28446939,
2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939,
2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939,
2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939, 2.28446939,
2.28446939, 4.56893878, 4.568938778, 6.853408167, 4.56893878,
6.85340817, 4.56893878, 6.85340817, 2.28446939, 4.56893878, 4.568938778,
2.284469389, 4.56893878, 6.85340817, 4.56893878, 4.56893878,
6.85340817, 4.56893878, 2.28446939, 4.56893878, 2.28446939, 4.56893878
)), .Names = c("year", "size", "distance", "taken", "mass"), class =
"data.frame", row.names = c(NA,
-550L))
-----Original Message-----
From: Ben Bolker [mailto:bbolker at gmail.com]
Sent: Friday, April 08, 2011 4:15 PM
To: Stratford, Jeffrey
Cc: r-sig-ecology at r-project.org
Subject: Re: [R-sig-eco] zero-truncated Poisson
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA1
On 04/08/2011 04:10 PM, Stratford, Jeffrey wrote:
> Hi everyone,
>
> I'm attempting to run a zero-truncated Poisson using VGAM and I run
into
> this error:
>
> Error in if ((temp <- sum(wz[, 1:M, drop = FALSE] < wzepsilon)))
> warning(paste(temp, :
> argument is not interpretable as logical
>
> Here's the code I'm using
>
> blja <- read.csv("g:\\blja\\blja.csv", header=T)
> library(VGAM)
> glm1 <- vglm(blja$taken ~ blja$mass + blja$year,family=pospoisson,
> data=blja)
Just a *very* quick suggestion: try
glm1 <- vglm(taken ~ mass + year,family=pospoisson, data=blja)
and see if that helps.
Also try summary() on your data (and/or sapply(blja,class))
to see if your data types are what you think they are (hint: R
often converts numeric data to factors if it has glitches in it)
If neither of those helps, could you use dput() to post your data (or
a subset thereof) in an easier-to-use format?
>
> We're looking at the number of acorns taken by jays using year (two
> years) and how much (mass) they're taking.
>
> Our data looks like this:
>
> year size distance taken mass
> one small 30.8735 10 13.8758
> one small 121.505 2 2.77516
> one small 46.055 12 16.65096
> one small 46.055 1 1.38758
> one small 46.055 4 5.55032
> one small 9.343 1 1.38758
> one small 46.055 10 13.8758
> one small 46.055 3 4.16274
> one small 46.055 5 6.9379
> one small 85.271 5 6.9379
> one small 85.271 1 1.38758
> one small 85.271 5 6.9379
> one small 85.271 3 4.16274
> ...
>
> Any suggestions (and alternatives!) would be appreciated!
>
> Thanks a bunch,
>
> Jeff
>
> ************************************
> Dr. Jeffrey A. Stratford
> Department of Health and Biological Sciences
> 84 W. South Street
> Wilkes University, PA 18766
> jeffrey.stratford at wilkes.edu
> 570-408-4761 (office)
> 570-332-2942 (cell)
> http://web.wilkes.edu/jeffrey.stratford/
> ************************************
>
>
>
> [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-ecology mailing list
> R-sig-ecology at r-project.org
> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
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