我遇到了 R INLA 没有计算拟合边际值的问题。我首先使用自己的数据集获得它，并且能够按照本书中的示例重现它。我怀疑一定有一些配置需要更改，或者 INLA 可能无法在后台正常工作？无论如何，这里是代码：
library("rgdal")
boston.tr <- readOGR(system.file("shapes/boston_tracts.shp",
package="spData")[1])
#create adjacency matrices
boston.adj <- poly2nb(boston.tr)
W.boston <- nb2mat(boston.adj, style = "B")
W.boston.rs <- nb2mat(boston.adj, style = "W")
boston.tr$CMEDV2 <- boston.tr$CMEDV
boston.tr$CMEDV2 [boston.tr$CMEDV2 == 50.0] <- NA
#define formula
boston.form <- log(CMEDV2) ~ CRIM + ZN + INDUS + CHAS + I(NOX^2) + I(RM^2) +
AGE + log(DIS) + log(RAD) + TAX + PTRATIO + B + log(LSTAT)
boston.tr$ID <- 1:length(boston.tr)
#run model
boston.iid <- inla(update(boston.form, . ~. + f(ID, model = "iid")),
data = as.data.frame(boston.tr),
control.compute = list(dic = TRUE, waic = TRUE, cpo = TRUE),
control.predictor = list(compute = TRUE)
)
当我查看该模型的输出时，它表明拟合值是计算出来的：
summary(boston.iid)
Call:
c("inla(formula = update(boston.form, . ~ . + f(ID, model = \"iid\")), ", " data = as.data.frame(boston.tr),
control.compute = list(dic = TRUE, ", " waic = TRUE, cpo = TRUE), control.predictor = list(compute = TRUE))"
)
Time used:
Pre = 0.981, Running = 0.481, Post = 0.0337, Total = 1.5
Fixed effects:
mean sd 0.025quant 0.5quant 0.975quant mode kld
(Intercept) 4.376 0.151 4.080 4.376 4.672 4.376 0
CRIM -0.011 0.001 -0.013 -0.011 -0.009 -0.011 0
ZN 0.000 0.000 -0.001 0.000 0.001 0.000 0
INDUS 0.001 0.002 -0.003 0.001 0.006 0.001 0
CHAS1 0.056 0.034 -0.010 0.056 0.123 0.056 0
I(NOX^2) -0.540 0.107 -0.751 -0.540 -0.329 -0.540 0
I(RM^2) 0.007 0.001 0.005 0.007 0.010 0.007 0
AGE 0.000 0.001 -0.001 0.000 0.001 0.000 0
log(DIS) -0.143 0.032 -0.206 -0.143 -0.080 -0.143 0
log(RAD) 0.082 0.018 0.047 0.082 0.118 0.082 0
TAX 0.000 0.000 -0.001 0.000 0.000 0.000 0
PTRATIO -0.031 0.005 -0.040 -0.031 -0.021 -0.031 0
B 0.000 0.000 0.000 0.000 0.001 0.000 0
log(LSTAT) -0.329 0.027 -0.382 -0.329 -0.277 -0.329 0
Random effects:
Name Model
ID IID model
Model hyperparameters:
mean sd 0.025quant 0.5quant 0.975quant mode
Precision for the Gaussian observations 169.24 46.04 99.07 160.46 299.72 141.30
Precision for ID 42.84 3.40 35.40 43.02 49.58 43.80
Deviance Information Criterion (DIC) ...............: -996.85
Deviance Information Criterion (DIC, saturated) ....: 1948.94
Effective number of parameters .....................: 202.49
Watanabe-Akaike information criterion (WAIC) ...: -759.57
Effective number of parameters .................: 337.73
Marginal log-Likelihood: 39.74
CPO and PIT are computed
Posterior marginals for the linear predictor and
the fitted values are computed
然而，当我尝试检查那些拟合的边际值时，那里什么也没有：
> boston.iid$marginals.fitted.values
NULL
有趣的是，我确实得到了后验的总结，所以它们一定是通过某种方式计算的？
> boston.iid$summary.fitted.values
mean sd 0.025quant 0.5quant 0.975quant mode
fitted.Predictor.001 2.834677 0.07604927 2.655321 2.844934 2.959994 2.858717
fitted.Predictor.002 3.020424 0.08220780 2.824525 3.034319 3.149766 3.052558
fitted.Predictor.003 3.053759 0.08883760 2.841738 3.071530 3.188051 3.094010
fitted.Predictor.004 3.032981 0.09846662 2.801099 3.056692 3.175215 3.084842
关于我在通话中错误指定的内容的任何想法。我已经设置了compute = T我在 R-INLA 论坛上看到的导致问题的原因。
小智 5
开发人员故意禁用边际计算，以使模型更快。
要启用它，您可以将这些添加到inla参数中：
control.predictor=list(compute=TRUE)
control.compute=list(return.marginals.predictor=TRUE)
所以它看起来像这样：
boston.form <- log(CMEDV2) ~ CRIM + ZN + INDUS + CHAS + I(NOX^2) + I(RM^2) +
AGE + log(DIS) + log(RAD) + TAX + PTRATIO + B + log(LSTAT)
boston.tr$ID <- 1:length(boston.tr)
#run model
boston.iid <- inla(update(boston.form, . ~. + f(ID, model = "iid")),
data = as.data.frame(boston.tr),
control.compute = list(dic = TRUE, waic = TRUE, cpo = TRUE, return.marginals.predictor=TRUE),
control.predictor = list(compute = TRUE)
)
boston.iid$summary.fitted.values
boston.iid$marginals.fitted.values