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Poisson GLMM
An example of the geostatistical approach to spatial modelling. The response distribution is Poisson with an isotropic correlation function r(d), where "d" is the distiance between two locations.
R - ADMB interface for mixed models
Explains how to set up a general mixed model interface between R and ADMB used for instance in glmmADMB
R stuff
Random scale
Distance Sampling with Random Scale Detection Function
Survey sampling related examples
Separable: Method explanation
It has for a long time been possible to fit GLMMs (Generalized Linear Mixed Models) in ADMB-RE. A typical example is correlated count data with Poisson distribution. However, when the observation are located on a spatial grid the number of latent variables (random effects in the ADMB-RE terminology) grows quadratically in the number of grid points in each geographical direction. The large number of random effects causes a computational challenge.
Simple examples
Skate mortality: Bayesian state-space model
Bayesian state-space model example from the NCEAS non-linear modelling working group
Spatial models
ADMB supports both the geostatistical approach and Gaussian Markov random field approach to spatial modelling
Different aspects of spline models
Splines I
notes and examples related to cubic splines
State-space models
Stochastic volatility collection
Stochastic volatility models for financial time series
Stochastic volatility models are used in mathematical finance to describe the evolution of asset returns, which typically exhibit changing variances over time.
Physical storage of individual examples with guarantied permanent URL
Survival analysis
Lifetime data and survival analysis
SV models with leverage effect
Tadpole mortality as a function of size
A maximum likelihood estimation problem with a binomial response variable, example from the NCEAS non-linear modelling working group.
Text books
Collections of examples taken from text books
The basic SV model and simple extensions
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