Count data can be analyzed using generalized linear mixed models when observations are
correlated in ways that require random effects. However, count data are often zero-inflated, …

Many criteria for statistical parameter estimation, such as maximum likelihood, are formulated
as a nonlinear optimization problem. Automatic Differentiation Model Builder (ADMB) is a …

Indices of abundance are the bedrock for stock assessments or empirical management
procedures used to manage fishery catches for fish populations worldwide, and are generally …

Ecological phenomena are often measured in the form of count data. These data can be
analyzed using generalized linear mixed models (GLMMs) when observations are correlated in …

The nonlinear filtering problem occurs in many scientific areas. Sequential Monte Carlo
solutions with the correct asymptotic behavior such as particle filters exist, but they are …

Fitting of non-Gaussian hierarchical random effects models by approximate maximum likelihood
can be made automatic to the same extent that Bayesian model fitting can be automated …

… This work was initiated when Hans J. Skaug and Mark Bravington were sabbatical visitors
to the Center for Stock Assessment Research (CSTAR), a partnership between UCSC and …

Predicting and explaining the distribution and density of species is one of the oldest concerns
in ecology. Species distributions can be estimated using geostatistical methods, which …

Identifying the existence and magnitude of density dependence is one of the oldest concerns
in ecology. Ecologists have aimed to estimate density dependence in population and …

The differences in demographic and life-history processes between organisms living in the
same population have important consequences for ecological and evolutionary dynamics. …