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Selected List of Latent Models, Likelihoods, Priors and Vignettes found in INLA:
Selected Latent Models with Example on each:
Autoregressive Model of Order 1
Autoregressive Model of Order p
Besag model for spatial effects
The dMatern model
Generic0 model
Correlated random effects: iid
Random walk model of order 1
Random walk model of order 2
Model for Seasonal Variation
The Lognormal-distribution
Spatial lag model for spatial effects
+ More below in the code
Selected Priors with Example on each:
Beta Prior for Correlation Parameters
Dirichlet Prior
“Expression”: a do-it-yourself prior
Gaussian Prior
Logit-Beta Prior
PC prior for the Correlation ρ with ρ = 0 as the base-model
PC prior for the correlation ρ with ρ = 1 as the base-model
PC prior for the degrees of freedom (dof)
PC prior for θ = ± log(a) in the Gamma - distribution Γ(1/a, 1/a) with base model a = 0
PC Prior for Precision
+ More below in the code
Selected Likelihoods with Simulated Example on each:
The Beta-distribution
The Beta-Binomial distribution
The Binomial-distribution
The Censored Poisson-distribution
The Exponential-distribution
The Gamma-distribution
The Gaussian-distribution
The Logistic-distribution
The Lognormal-distribution
The Poisson-distribution
+ More below in the code
Vignettes in INLA:
SPDE one dimensional example
A Short Introduction on how to fit a SPDE Model with INLA
Blended GEV: a tutorial using R-INLA
Conditional Sampling from a Fitted Model
Conditional Logistic Regression Model
User Defined Integration Points
Defining a Latent Model in R: The rgeneric model
Multinomial logit models with INLA
Approximating Joint Marginals in R-INLA
Tutorial: Scaling IGMRF-models in R-INLA
To get all Latent Models, likelihoods and priors found in INLA, use the following commands in R:
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