inlabru: plot.bru – R documentation

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plot.bru

Plot method for posterior marginals estimated by bru

Description

bru() uses INLA::inla() to fit models. The latter estimates the posterior densities of all random effects in the model. This function serves to access and plot the posterior densities in a convenient way.

Usage

## S3 method for class 'bru'
plot(x, ...)

Arguments

`x`	a fitted `bru()` model.
`...`	A character naming the effect to plot, e.g. "Intercept". For random effects, adding `index = ...` plots the density for a single component of the latent model.

Value

an object of class gg

Examples

## Not run: 

# Generate some data and fit a simple model
input.df <- data.frame(x = cos(1:10))
input.df <- within(input.df, y <- 5 + 2 * cos(1:10) + rnorm(10, mean = 0, sd = 0.1))
fit <- bru(y ~ x, family = "gaussian", data = input.df)
summary(fit)

# Plot the posterior of the model's x-effect
plot(fit, "x")

## End(Not run)

inlabru

Bayesian Latent Gaussian Modelling using INLA and Extensions

v2.3.1

GPL (>= 2)

Authors

Finn Lindgren [aut, cre, cph] (<https://orcid.org/0000-0002-5833-2011>, Finn Lindgren continued development of the main code), Fabian E. Bachl [aut, cph] (Fabian Bachl wrote the main code), David L. Borchers [ctb, dtc, cph] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb, cph] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb, dtc, cph] (Lindesay Scott-Howard provided MRSea data import code), Seaton Andy [ctb] (Andy Seaton provided testing and bugfixes)

Initial release