Linked Life Data

11550920

Source:http://linkedlifedata.com/resource/pubmed/id/11550920

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2001-9-11
pubmed:abstractText
Certain probability models sometimes provide poor descriptions when fitted to data by maximum likelihood. We examine one such model for the survival of wild animals, which is fitted to two sets of data. When the model behaves poorly, its expected information matrix, evaluated at the maximum likelihood estimate of parameters, has a 'small' smallest eigenvalue. This is due to the fitted model being similar to a parameter-redundant submodel. In this case, model parameters that are precisely estimated have small coefficients in the eigenvector corresponding to the smallest eigenvalue. Approximate algebraic expressions are provided for the smallest eigenvalue. We discuss the general applicability of these results.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0006-341X
pubmed:author
pubmed:issnType
Print
pubmed:volume
57
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
720-6
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2001
pubmed:articleTitle
On the near-singularity of models for animal recovery data.
pubmed:affiliation
School of Mathematics and Statistics, University College UNSW, Australian Defence Force Academy, Canberra ACT. e-catchpole@adfa.edu.au
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't