James-Thorson
commented
9 years ago So first I would try using the bias-correction tool for an unbiased estimate of N. Try running
SD = sdreport( obj, bias.correct=TRUE ) SD$unbiased$value
cheers, jim
On Fri, Jul 31, 2015 at 10:44 AM, Daniel J. Hocking < notifications@github.com> wrote:
When using the Poisson (jnll = -dnorm(count_ip, N_i*detect_ip)) rather than a binomial/multinomial (e.g. count ~ bin(N, detect)), it's possible for the resulting abundance (N which is lambda_ip in the code) to be lower than the sum of the removal captures. This isn't ideal because we have data with blocknets so tresspass should be essentially 0 and the population should be completely closed so we know that the abundances is at least the sum of the captures (c_sum). In our case, 6 of the ~25 sites have estimated abundances lower than c_sum.
Here's the results:
c_sum N_i problem pass_1 pass_2 pass_3 1 2 5.64692914 FALSE 2 0 0 2 19 16.59943823 TRUE 13 6 0 3 5 10.45871664 FALSE 4 1 0 4 4 5.87692710 FALSE 3 0 1 5 41 39.09965187 TRUE 36 5 0 6 60 67.33948789 FALSE 29 22 9 7 74 75.90026910 FALSE 54 16 4 8 29 30.81556512 FALSE 16 7 6 9 3 5.34360595 FALSE 2 1 0 10 21 20.97239012 TRUE 14 2 5 11 29 31.97828711 FALSE 16 5 8 12 1 3.13212761 FALSE 0 1 0 13 62 61.12344278 TRUE 48 9 5 14 20 21.74247106 FALSE 15 5 0 15 6 8.95806693 FALSE 4 2 0 16 23 23.47056684 FALSE 16 6 1 17 13 13.99877807 FALSE 9 3 1 18 16 16.59556384 FALSE 9 5 2 19 9 12.23351022 FALSE 4 1 4 20 7 3.77940218 TRUE 5 2 0 21 8 8.12085111 FALSE 7 1 0 22 1 1.00927762 FALSE 1 0 0 23 1 1.60131358 FALSE 0 1 0 24 1 0.03617079 TRUE 1 0 0
— Reply to this email directly or view it on GitHub https://github.com/djhocking/Trout_GRF/issues/2.
djhocking
When using the Poisson (
jnll = -dnorm(count_ip, N_i*detect_ip)) rather than a binomial/multinomial (e.g.count ~ bin(N, detect)), it's possible for the resulting abundance (Nwhich islambda_ipin the code) to be lower than the sum of the removal captures. This isn't ideal because we have data with blocknets so tresspass should be essentially 0 and the population should be completely closed so we know that the abundances is at least the sum of the captures (c_sum). In our case, 6 of the ~25 sites have estimated abundances lower thanc_sum. It's generally quite close, sometimes even rounding would alleviate the issue, so I'm not overly concerned. But as a methods paper it would be worth thinking about some more.Here's the results: