A heteroskedastic error covariance matrix estimator using a first-order conditional autoregressive Markov simulation for deriving asympotical efficient estimates from ecological sampled Anopheles arabiensis aquatic habitat covariates

BACKGROUND: Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Jacob, Benjamin G, Griffith, Daniel A, Muturi, Ephantus J, Caamano, Erick X, Githure, John I, Novak, Robert J
Format: Artigo
Langue:Inglês
Publié: BioMed Central 2009
Sujets:
Research
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC2760564/
https://ncbi.nlm.nih.gov/pubmed/19772590
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1475-2875-8-216
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires