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New PDF release: Analysis of Capture-Recapture Data

By McCrea, Rachel S.

ISBN-10: 1439836590

ISBN-13: 9781439836590

ISBN-10: 1439836604

ISBN-13: 9781439836606

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It may arise that likelihoods are not flat, but nearly so, near the maximum, and such a feature may be evident in the correlations between estimators. 3 The EM algorithm The EM algorithm may be used to seek maximum-likelihood estimates in applications when there are missing data. The algorithm is iterative, each step involving both an expectation (E) and a maximisation (M). In some cases it is obvious that there are data missing, whereas in others, when fitting mixture models for example, it may not be immediately apparent that the problem can be formulated as a missing-data problem.

M, where Ik is an information criterion. However, frequently not all models will fit the data well, and also if individual models make different predictions then it is important to know that, so that model averaging should not be done routinely, and without considering the results of fitting component models. An illustration of this is provided by King et al. (2008), involving models for the survival of Northern lapwings, Vanellus vanellus, and a further illustration will be provided in Chapter 3.

The book by Caswell (2001) is the classical reference for population dynamics modelling, and provides information regarding the formation of Leslie matrices. A modern approach to sensitivity analysis in population modelling is provided by Miller et al. (2011a). A wider ecological perspective is provided by references such as Morgan et al. (1997), Furness and Greenwood (1993), Clutton-Brock (1988), Clutton-Brock and Albon (1989) and Clutton-Brock et al. (1982). FURTHER READING 9 The article by Morgan and Viallefont (2012) gives a number of websites which are rich sources of data on birds, including discussion of motivation and sampling methods.

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Analysis of Capture-Recapture Data by McCrea, Rachel S.

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