Ed,

I've held off on replying to this post because I'm not familiar with

RCapture, but I thought I'd jump in as no one else.

The answer is that, yes, your sample size is too small. What is

happening is that the maximum likelihood estimates for the capture

probabilities lie on the boundary of the parameter space -- they are

exactly equal to one. Unfortunately, the approximate normality of

maximum likelihood estimates breaks down at this point, so the standard

errors don't make sense. Computing standard errors from the usual

approximation (inverse information matrix) results in standard errors of

0 for the capture probabilities -- suggesting that there is no

uncertainty. This in turn means that there is no uncertainty in

abundance. If the capture probabilities were truly 1 with no uncertainty

then you would definitely have captured every individual in the

population and you would know the abundance exactly. Clearly that's not

true.

The reason for this is that your sample is too small. Note that most of

the individuals were never recaptured and that there was never a gap

between captures -- individuals were recaptured on subsequent occasions

until they were never seen again. This is perfectly consistent with the

inference that capture is perfect and individuals are seen on every

occasion until they leave the population, which is what the results are

telling you.

My guess is that this may be close to the truth and, by chance with the

small sample, you have hit a data set that leads to boundary estimates.

Is it reasonable to believe that this species has a fairly short

life-span (relative to the time between captures) and that the capture

probability is high?

One solution is to use profile likelihood intervals to compute estimates

of uncertainty for the parameters on the boundary (the p's). Again, I

don't know about RCapture, but this is possible in Program MARK.

Alternatively, you could work with a Bayesian analysis using a prior

selected to keep the parameters away from the boundary.

I hope this helps.

Cheers,

Simon

On 2016-09-15 2:00 PM, McGinley, Ed wrote:

--

Simon Bonner

Assistant Professor of Environmetrics/Director MMASc

Department of Statistical and Actuarial Sciences/Department of Biology

University of Western Ontario

Office: Western Science Centre rm 276

Email:

[hidden email] | Telephone: 519-661-2111 x88205 | Fax: 519-661-3813

Twitter: @bonnerstatslab | Website:

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