########################################################################
# Robust Regression. T dist (df >=2)
########################################################################
model
{
for(i
in 1:n)
{
y[i]
<- sqrt(buchanan[i])
x[i]
<- sqrt(perot[i])
y[i]
~ dt(mu[i], taui, 4) # likelihood of t-dist with df=4
mu[i]
<- b[1] + b[2]*x[i]
}
#priors
b[1] ~ dnorm(0, 0.000001)
b[2] ~ dnorm(0, 0.000001)
tau ~ dgamma(0.001, 0.001)
sigma
<- 1/tau
#
prediction of mean response for x=18, 20,..., 196
for(i
in 1:90)
{
x_p[i] <- 18+2*(i-1)
mu_p[i]
<- b[1] + b[2]*x_p[i]
}
}
# Initial values. Load below values and "gen
inits"
list(
b = c(0, 0), tau=1 )
# Data
list(n
= 67)
# Data
perot[] buchanan[]
8072 262
667 73
5922
248
819 65
25249 570
38964 789
630 90
7783
182
7244
270
3281
186
6320
122
1970 89
965 36
652 29
13844 652
8587 504
2185 83
878 33
938 39
841 29
521
9
1054 71
406 23
851 30
1135 22
7272
242
3739
127
25154 847
1208 76
4635
105
1602 102
393 29
316 10
8813
289
18389 305
6672
282
1774 67
376 39
578 29
10360 272
11340 563
5005
108
24722 560
4817 47
1657 90
5432 267
1666 43
18191 446
6091
145
30739 3407
18011 570
36990 1010
14991 538
3272
148
4957
311
14939 305
9357
194
4205
229
8482
124
2375
114
1874 108
1140 27
425 29
17319 396
1091 46
2342
120
1287 88
END