ggplot_inla_residuals2: Plot residuals against covariate values for INLA model using...

In timcdlucas/INLAutils: Utility Functions for 'INLA'

Plot residuals against covariate values for INLA model using ggplot2

Description

Plot residuals against covariate values for INLA model using ggplot2

Usage

ggplot_inla_residuals2(
  inla.model,
  observed,
  CI = FALSE,
  se = TRUE,
  method = "auto"
)

Arguments

inla.model	An inla object
observed	The observed values
CI	plot credible intervals for each residual
se	Plot a ribbon showing the standard error of the smoother.
method	What method should be used for the smoother. Defaults to loess unless data is large. Other options include 'gam', 'loess', 'lm'. See geom_smooth for details.

Examples

## Not run: 
 library(INLA)
 data(Epil)
 observed <- Epil[1:30, 'y']
 Epil <- rbind(Epil, Epil[1:30, ])
 Epil[1:30, 'y'] <- NA
 ## make centered covariates
 formula = y ~ Trt + Age + V4 +
          f(Ind, model="iid") + f(rand,model="iid")
 result = inla(formula, family="poisson", data = Epil, 
               control.predictor = list(compute = TRUE, link = 1))
 ggplot_inla_residuals2(result, observed)
 

 data(Seeds)
 l <- nrow(Seeds)
 Seeds <- rbind(Seeds, Seeds)
 Seeds$r[1:l] <- NA


 formula = r ~ x1 * x2 + f(plate, model = "iid")
 mod.seeds = inla(formula, data=Seeds, family = "binomial", Ntrials = n, 
                  control.predictor = list(compute = TRUE, link = 1))
 ggplot_inla_residuals2(mod.seeds, na.omit(Seeds$r / Seeds$n), method = 'lm')
 
## End(Not run)

timcdlucas/INLAutils documentation built on Nov. 29, 2022, 5:41 a.m.