Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations
Robb, Matthew L. and Böhning, Dankmar (2011) Imputing unobserved values with the EM algorithm under left and right-truncation, and interval censoring for estimating the size of hidden populations. Biometrical Journal, 53, (1), 75-87. (doi:10.1002/bimj.201000004).
Full text not available from this repository.
Capture–recapture techniques have been used for considerable time to predict population size. Estimators usually rely on frequency counts for numbers of trappings; however, it may be the case that these are not available for a particular problem, for example if the original data set has been lost and only a summary table is available. Here, we investigate techniques for specific examples; the motivating example is an epidemiology study by Mosley et al., which focussed on a cholera outbreak in East Pakistan. To demonstrate the wider range of the technique, we also look at a study for predicting the long-term outlook of the AIDS epidemic using information on number of sexual partners. A new estimator is developed here which uses the EM algorithm to impute unobserved values and then uses these values in a similar way to the existing estimators. The results show that a truncated approach – mimicking the Chao lower bound approach – gives an improved estimate when population homogeneity is violated
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||Faculty of Social and Human Sciences > Southampton Statistical Sciences Research Institute
Faculty of Social and Human Sciences > Mathematical Sciences > Statistics
|Date Deposited:||09 Feb 2012 11:45|
|Last Modified:||09 Feb 2012 13:10|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)