View source: R/plot_inla_residuals.R

ggplot_inla_residuals2 | R Documentation |

Plot residuals against covariate values for INLA model using ggplot2

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

`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 |

## 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)

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