Space—time zero‐inflated count models of Harbor seals

By Jay M. Ver Hoef, J. K. Jansen. 2007

110 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering

View Paper: https://www.semanticscholar.org/paper/8a71903d1aef2f296abf553f681cc06f990cf1a9

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In Atmospheric Science

In Environmental Engineering

Citations in the corpus

Mixed Effects Models and Extensions in Ecology with R (2009, methodology): “(2006), Verbeke and Molenberghs (2000), or Pinheiro and Bates (2000).”
The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models (2014, background): “…in Bayesian Markov Chain Monte Carlo (MCMC) simulation approaches, which remain cumbersome, require extensive simulation, are time consuming, and pose convergence assessment problems as the number of dimensions increases (see Ver Hoef and Jansen, 2007, and Franzese et al., 2010 for discussions).”
Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern (2012, methodology): “Therefore, we used a hurdle model approach (Martin et al. 2005; ver Hoef & Jansen 2007), which is a two-step process.”
Trend estimation in populations with imperfect detection (2009, methodology): “As the quantities in our model have an explicit biological meaning, our model is an explicit, or mechanistic, hierarchical model (Royle & Dorazio 2008), in contrast to the mechanistically more implicit hierarchical models of Link & Sauer (2002), Lande et al. (2003), Dennis et al. (2006), Ver Hoef &”
Spatial semiparametric models improve estimates of species abundance and distribution (2014, methodology): “The models are known in the fisheries literature as delta generalized linear mixed models ( -GLMM; Stefánsson 1996; Maunder and Punt 2004) and more generally as hurdle models (Ver Hoef and Jansen 2007).”
A latent variable representation of count data models to accommodate spatial and temporal dependence: application to predicting crash frequency at intersections (2011, methodology): “Specifically, under usual regularity assumptions (Molenberghs and Verbeke, 2005, page 191, Xu and Reid, 2011), the CML estimator of θ is consistent and asymptotically normal distributed with asymptotic mean θ and covariance matrix given by the inverse of Godambe’s (1960) sandwich information matrix ”