Using hidden Markov models to deal with availability bias on line transect surveys.
Biometrics
; 69(3): 703-13, 2013 Sep.
Article
en En
| MEDLINE
| ID: mdl-23848543
We develop estimators for line transect surveys of animals that are stochastically unavailable for detection while within detection range. The detection process is formulated as a hidden Markov model with a binary state-dependent observation model that depends on both perpendicular and forward distances. This provides a parametric method of dealing with availability bias when estimates of availability process parameters are available even if series of availability events themselves are not. We apply the estimators to an aerial and a shipboard survey of whales, and investigate their properties by simulation. They are shown to be more general and more flexible than existing estimators based on parametric models of the availability process. We also find that methods using availability correction factors can be very biased when surveys are not close to being instantaneous, as can estimators that assume temporal independence in availability when there is temporal dependence.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Cadenas de Markov
/
Modelos Estadísticos
/
Biometría
Tipo de estudio:
Health_economic_evaluation
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Animals
Idioma:
En
Revista:
Biometrics
Año:
2013
Tipo del documento:
Article
País de afiliación:
Reino Unido
Pais de publicación:
Estados Unidos