1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
|
params <-
list(EVAL = TRUE)
## ----SETTINGS-knitr, include=FALSE--------------------------------------------
stopifnot(require(knitr))
opts_chunk$set(
comment=NA,
eval = if (isTRUE(exists("params"))) params$EVAL else FALSE,
dev = "png",
dpi = 150,
fig.asp = 0.618,
fig.width = 5,
out.width = "60%",
fig.align = "center"
)
## ----setup, message=FALSE-----------------------------------------------------
library("rstanarm")
library("bayesplot")
library("loo")
## ----data---------------------------------------------------------------------
# the 'roaches' data frame is included with the rstanarm package
data(roaches)
str(roaches)
# rescale to units of hundreds of roaches
roaches$roach1 <- roaches$roach1 / 100
## ----count-roaches-mcmc, results="hide"---------------------------------------
fit1 <-
stan_glm(
formula = y ~ roach1 + treatment + senior,
offset = log(exposure2),
data = roaches,
family = poisson(link = "log"),
prior = normal(0, 2.5, autoscale = TRUE),
prior_intercept = normal(0, 5, autoscale = TRUE),
seed = 12345
)
## ----loo1---------------------------------------------------------------------
loo1 <- loo(fit1, save_psis = TRUE)
## ----print-loo1---------------------------------------------------------------
print(loo1)
## ----plot-loo1, out.width = "70%"---------------------------------------------
plot(loo1)
## ----ppc_loo_pit_overlay------------------------------------------------------
yrep <- posterior_predict(fit1)
ppc_loo_pit_qq(
y = roaches$y,
yrep = yrep,
lw = weights(loo1$psis_object)
)
## ----count-roaches-negbin, results="hide"-------------------------------------
fit2 <- update(fit1, family = neg_binomial_2)
## ----loo2---------------------------------------------------------------------
loo2 <- loo(fit2, save_psis = TRUE, cores = 2)
print(loo2)
## ----plot-loo2----------------------------------------------------------------
plot(loo2, label_points = TRUE)
## ----reloo--------------------------------------------------------------------
if (any(pareto_k_values(loo2) > 0.7)) {
loo2 <- loo(fit2, save_psis = TRUE, k_threshold = 0.7)
}
print(loo2)
## ----ppc_loo_pit_overlay-negbin-----------------------------------------------
yrep <- posterior_predict(fit2)
ppc_loo_pit_qq(roaches$y, yrep, lw = weights(loo2$psis_object))
## ----loo_compare--------------------------------------------------------------
loo_compare(loo1, loo2)
|
