-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathexample.R
137 lines (118 loc) · 3.44 KB
/
example.R
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
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
choice <- 7
run_dic <- TRUE
source("models.R")
s7 <- s
s7$summary$statistics[grepl("avsigma", rownames(s7$summary$statistics)),"Mean"]
dic7 <- dic
choice <- 19
source("models.R")
s19 <- s
s19$summary$statistics[grepl("avsigma", rownames(s19$summary$statistics)),"Mean"]
dic19 <- dic
sum(dic19$deviance+dic19$penalty)
choice <- 8
run_dic <- FALSE
source("models.R")
s8 <- s
s8$summary$statistics[grepl("dof", rownames(s8$summary$statistics)),]
s8$summary$statistics[grepl("avsigma", rownames(s8$summary$statistics)),"Mean"]
for (i in 1:nt)
for (j in 1:nt)
ttrI[i,j] <- s8$summaries[grepl(paste0("avsigma\\[",i,",",j,"\\]"), rownames(s8$summary$statistics)),"Mean"]
choice <- 20
run_dic <- TRUE
source("modelf.R")
sp <- s
sp$summaries[grepl("dof", rownames(sp$summary$statistics)),]
sp$summaries[grepl("ve", rownames(sp$summary$statistics)),]
sp$summaries[grepl("sigma", rownames(sp$summary$statistics)),"Mean"]
dicp <- dic
sum(dicp$deviance+dicp$penalty)
# Mean deviance: 4625
# penalty 320.7
# Penalized deviance: 4946
st <- sp$summary$statistics
ttrs <- array(NA,c(9,4,4))
ttrmean <- matrix(0,4,4)
for (k in 1:9)
{
for (i in 1:nt)
for (j in 1:nt)
ttrs[k,i,j] <- st[grepl(paste0("sigma\\[",k,",",i,",",j,"\\]"),
rownames(st)),"Mean"]
ttrmean <- ttrmean + ttrs[k,,] / 9
}
# Mean deviance: 4592
# penalty 333
# Penalized deviance: 4925.215
# No ve
source("models.R")
s20 <- s
s20$summary$statistics[grepl("dof", rownames(s20$summary$statistics)),]
s20$summary$statistics[grepl("sigma", rownames(s20$summary$statistics)),"Mean"]
dic20 <- dic
sum(dic20$deviance+dic20$penalty)
st <- s20$summary$statistics
ttrs20 <- array(NA,c(9,4,4))
ttrmean20 <- matrix(0,4,4)
for (k in 1:9)
{
for (i in 1:nt)
for (j in 1:nt)
ttrs20[k,i,j] <- st[grepl(paste0("sigma\\[",k,",",i,",",j,"\\]"),
rownames(st)),"Mean"]
ttrmean20 <- ttrmean20 + ttrs20[k,,] / 9
}
# Mean deviance: 4604
# penalty 328.7
# Penalized deviance: 4932.58
# With ve
choice <- 20
run_dic <- TRUE
source("models.R")
s20ve <- s
s20ve$summary$statistics[grepl("dof", rownames(s20ve$summary$statistics)),]
s20ve$summary$statistics[grepl("ve", rownames(s20ve$summary$statistics)),]
s20ve$summary$statistics[grepl("sigma", rownames(s20ve$summary$statistics)),"Mean"]
dic20ve <- dic
sum(dic20ve$deviance+dic20ve$penalty)
dic20ve
# Mean deviance: 4603
# penalty 328.7
# Penalized deviance: 4932.03
choice <- 19
run_dic <- TRUE
source("models.R")
s19 <- s
s19$summaries[grepl("dof", rownames(s19$summary$statistics)),]
s19$summary$statistics[grepl("sigma", rownames(s19$summary$statistics)),"Mean"]
dic19 <- dic
sum(dic19$deviance+dic19$penalty)
dic19
# Mean deviance: 4679
# penalty 316.9
# Penalized deviance: 4995.49
st <- s20ve$summary$statistics
ttrs20ve <- array(NA,c(9,4,4))
ttrmean20ve <- matrix(0,4,4)
for (k in 1:9)
{
for (i in 1:nt)
for (j in 1:nt)
ttrs20ve[k,i,j] <- st[grepl(paste0("sigma\\[",k,",",i,",",j,"\\]"),
rownames(st)),"Mean"]
ttrmean20ve <- ttrmean20ve + ttrs20ve[k,,] / 9
}
ttrmean20ve
choice <- 8
run_dic <- FALSE
source("modelf.R")
so <- s
so$summary$statistics[grepl("dof", rownames(so$summary$statistics)),]
so$summary$statistics[grepl("avsigma", rownames(so$summary$statistics)),"Mean"]
st <- so$summary$statistics
ttrO <- matrix(NA,4,4)
for (i in 1:nt)
for (j in 1:nt)
ttrO[i,j] <- st[grepl(paste0("avsigma\\[",i,",",j,"\\]"),
rownames(st)),"Mean"]