Estimation of the Negative Binomial Parameter κ by Maximum Quasi -Likelihood
- 1 March 1989
- journal article
- research article
- Published by JSTOR in Biometrics
- Vol. 45 (1) , 309-316
- https://doi.org/10.2307/2532055
Abstract
We investigate estimation of the parameter .kappa., of the negative binomial distribution for small samples, using a method-of-moments estimate (MME) and a maximum quasi-likelihood estimate (MQLE). Previous work is reviewed; the importance of indirect estimation of .kappa. through its recipirocal, .alpha., and of allowance for negative estimates of .kappa. (or .alpha.) are discussed. Samples of size 50 are simulated 10,000 times for each of several parameter combinations to examine the properties of the estimates. Samples of sizes 10, 20, 30, and 50 are simulated 1,000 times to investigate the effect of sample size. Both estimators perform reasonably well except when the mean is small and the sample size does not exceed 20. Three examples are given, one of a designed experiment, for which the MQLE is especially suited; confidence limits are derived for the MQLE. Further work along these lines is required for adequate assessment of the usual maximum likelihood estimate.This publication has 3 references indexed in Scilit:
- Behavioural Dynamics and the Negative Binomial DistributionOikos, 1986
- Stability of Real Interacting Populations in Space and Time: Implications, Alternatives and the Negative Binomial kcJournal of Animal Ecology, 1986
- Ades: New Ecological Families of Species-Specific Frequency Distributions that Describe Repeated Spatial Samples with an Intrinsic Power-Law Variance-Mean PropertyJournal of Animal Ecology, 1985