2 replaced http://stats.stackexchange.com/ with https://stats.stackexchange.com/
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In the process of answering this: http://stats.stackexchange.com/questions/123367/estimating-parameters-for-a-binomial/123748?noredirect=1#comment235901_123748Estimating parameters for a binomial I stumbled over this paper:

Ingram Olkin, A John Petkau, James V Zidek: A comparison of N estimators for the Binomial Distribution. Jasa 1981.

which gives an example where method of moments, at least in some cases, beats maximum likelihood. The problem is estimation of $N$ in the binomial distribution $\text{Bin}(N,p)$ where both parameters are unknown. It appears for example in trying to estimate animal abundance when you cannot see all the animals, and the sighting probability $p$ also is unknown.

In the process of answering this: http://stats.stackexchange.com/questions/123367/estimating-parameters-for-a-binomial/123748?noredirect=1#comment235901_123748 I stumbled over this paper:

Ingram Olkin, A John Petkau, James V Zidek: A comparison of N estimators for the Binomial Distribution. Jasa 1981.

which gives an example where method of moments, at least in some cases, beats maximum likelihood. The problem is estimation of $N$ in the binomial distribution $\text{Bin}(N,p)$ where both parameters are unknown. It appears for example in trying to estimate animal abundance when you cannot see all the animals, and the sighting probability $p$ also is unknown.

In the process of answering this: Estimating parameters for a binomial I stumbled over this paper:

Ingram Olkin, A John Petkau, James V Zidek: A comparison of N estimators for the Binomial Distribution. Jasa 1981.

which gives an example where method of moments, at least in some cases, beats maximum likelihood. The problem is estimation of $N$ in the binomial distribution $\text{Bin}(N,p)$ where both parameters are unknown. It appears for example in trying to estimate animal abundance when you cannot see all the animals, and the sighting probability $p$ also is unknown.

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source | link

In the process of answering this: http://stats.stackexchange.com/questions/123367/estimating-parameters-for-a-binomial/123748?noredirect=1#comment235901_123748 I stumbled over this paper:

Ingram Olkin, A John Petkau, James V Zidek: A comparison of N estimators for the Binomial Distribution. Jasa 1981.

which gives an example where method of moments, at least in some cases, beats maximum likelihood. The problem is estimation of $N$ in the binomial distribution $\text{Bin}(N,p)$ where both parameters are unknown. It appears for example in trying to estimate animal abundance when you cannot see all the animals, and the sighting probability $p$ also is unknown.