Closed ASeatonSpatial closed 3 years ago
This bug is fixed since at least 2.1.15:
> fml <- y ~ Intercept + myar1(t, model = "ar1", replicate = r)
> fit <- bru(fml, family = "poisson", data = df_groups)
> summary(fit)
inlabru version: 2.1.15.9000
INLA version: 20.12.10
Components:
Intercept: Model types main='linear', group='exchangeable', replicate='iid'
myar1: Model types main='ar1', group='exchangeable', replicate='iid'
Likelihoods:
Family: 'poisson'
Data class: 'data.frame'
Predictor: y ~ .
Time used:
Pre = 0.212, Running = 0.577, Post = 0.168, Total = 0.957
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
Intercept -0.242 0.236 -0.72 -0.237 0.213 -0.229 0
Random effects:
Name Model
myar1 AR1 model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for myar1 0.431 0.084 0.285 0.425 0.613 0.414
Rho for myar1 0.702 0.050 0.598 0.705 0.792 0.708
Expected number of effective parameters(stdev): 154.04(7.24)
Number of equivalent replicates : 1.95
Deviance Information Criterion (DIC) ...............: 894.60
Deviance Information Criterion (DIC, saturated) ....: 426.16
Effective number of parameters .....................: 145.77
Watanabe-Akaike information criterion (WAIC) ...: 869.96
Effective number of parameters .................: 91.34
Marginal log-Likelihood: -551.29
Posterior marginals for the linear predictor and
the fitted values are computed
Error when attempting to define a replicate of an ar1 model component.
Running the following code with the current backend development branch and INLA version 18.07.12 returns an error:
This returns:
This is attempting to fit a model with 3 replicates of n = 100 each.
Andy