Respected Sir
I tried the strucchange
My data is attached. However I tried the attached commands (last
save.txt) to perform Bai Perron 2003... I t worked well but in the end
it is giving warning that overlapping confidence interval... I am not
sure how to proceed... Please Help Me
Thanking You
Ayanendu Sanyal
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Thanking you
Ayanendu Sanyal
PhD Scholar
Institute for Social and Economic Change (ISEC)
P.O- Nagarbhavi
Bangalore-72
State- Karnataka
Country- India
PIN- 560072
www.isec.ac.in/phd.html
http://ayanendusanyal.blogspot.com/
t lnrpe
1 1.6113515
2 1.619601724
3 1.599889264
4 1.645954835
5 1.723777317
6 1.830606002
7 2.034751407
8 2.112377045
9 2.095050993
10 2.046822835
11 2.276628064
12 2.543864584
13 2.619425807
14 2.717786454
15 2.874537082
16 2.923223972
17 3.136825311
18 3.206377996
19 3.352655132
20 3.49032806
21 3.508602739
22 3.621768106
23 3.803617305
24 4.141727497
25 4.27471221
26 4.34523451
27 4.242555261
28 4.262046942
29 4.378894917
30 4.419018243
31 4.391496862
32 4.489015146
33 4.588180885
34 4.846861554
35 5.069645376
36 5.257766481
37 5.292695491
38 5.307844982
39 5.277006289
40 5.323613873
41 5.377629069
42 5.429256311
43 5.443411354
44 5.47242567
45 5.727392687
46 6.147054773
> ayan <- read.table("ayan.txt", header=T)
> x =read.table(file="ayan.txt",header=T)
> library(strucchange)
> bp.ayan <- breakpoints(x[["lnrpe"]] ~ x[["t"]])
> summary (bp.ayan)
Optimal (m+1)-segment partition:
Call:
breakpoints.formula(formula = x[["lnrpe"]] ~ x[["t"]])
Breakpoints at observation number:
m = 1 23
m = 2 23 33
m = 3 11 23 33
m = 4 11 23 33 40
m = 5 11 20 26 34 40
m = 6 8 14 20 26 34 40
Corresponding to breakdates:
m = 1 0.5
m = 2 0.5
m = 3 0.239130434782609 0.5
m = 4 0.239130434782609 0.5
m = 5 0.239130434782609 0.434782608695652 0.565217391304348
m = 6 0.173913043478261 0.304347826086956 0.434782608695652 0.565217391304348
m = 1
m = 2 0.717391304347826
m = 3 0.717391304347826
m = 4 0.717391304347826 0.869565217391304
m = 5 0.739130434782609 0.869565217391304
m = 6 0.739130434782609 0.869565217391304
Fit:
m 0 1 2 3 4 5
RSS 1.2131579 0.7466773 0.5243361 0.3570253 0.2712234 0.2589809
BIC -25.2008012 -36.0409283 -40.8160181 -47.0090984 -48.1669059 -38.8056613
m 6
RSS 0.2698858
BIC -25.4224766
> plot (bp.ayan)
> breakdates(bp.ayan)
[1] 0.2391304 0.5000000 0.7173913 0.8695652
> ci.ayan <- confint(bp.ayan)
> breakdates(ci.ayan)
2.5 % breakpoints 97.5 %
1 0.2173913 0.2391304 0.3260870
2 0.4782609 0.5000000 0.5217391
3 0.6956522 0.7173913 0.7391304
4 0.5434783 0.8695652 0.8913043
Warning message:
Overlapping confidence intervals
> ci.ayan
Confidence intervals for breakpoints
of optimal 5-segment partition:
Call:
confint.breakpointsfull(object = bp.ayan)
Breakpoints at observation number:
2.5 % breakpoints 97.5 %
1 10 11 15
2 22 23 24
3 32 33 34
4 25 40 41
Corresponding to breakdates:
2.5 % breakpoints 97.5 %
1 0.2173913 0.2391304 0.3260870
2 0.4782609 0.5000000 0.5217391
3 0.6956522 0.7173913 0.7391304
4 0.5434783 0.8695652 0.8913043
Warning message:
Overlapping confidence intervals
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