Break Points
Respected Sir Thank You for the ultra fast reply.... I changed the file and defined my data as time series and then ran 'strucchange'.... i have attached the lastsave1.txt file..... but the lines (ci.ayan) is not working.... Is the work ok???? please confirm .... I am not so much familar with this test... This time it didnt gave any warning message. Ayan
On Sat, Dec 31, 2011 at 2:45 AM, Achim Zeileis <Achim.Zeileis at uibk.ac.at> wrote:
On Fri, 30 Dec 2011, Ayanendu Sanyal wrote:
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
Overlapping confidence intervals typically indicate that too many breakpoints were selected and/or the model does not fit well. In your case, the BIC selection is probably not the best solution. hth, Z
Thanking You Ayanendu Sanyal -- Please have a look at our new mission and contribute into it (cut and paste the link below in the address bar of your internet browser) http://thesocialscienceinformer.blogspot.com/ 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/
Please have a look at our new mission and contribute into it (cut and paste the link below in the address bar of your internet browser) http://thesocialscienceinformer.blogspot.com/ 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/ -------------- next part -------------- R version 2.14.1 (2011-12-22) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i386-pc-mingw32/i386 (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(strucchange) Loading required package: zoo Attaching package: ?zoo? The following object(s) are masked from ?package:base?: as.Date, as.Date.numeric Loading required package: sandwich > ayan <- read.table("ayan.txt", header=T) > ayan lnrpe 1 1.611352 2 1.619602 3 1.599889 4 1.645955 5 1.723777 6 1.830606 7 2.034751 8 2.112377 9 2.095051 10 2.046823 11 2.276628 12 2.543865 13 2.619426 14 2.717786 15 2.874537 16 2.923224 17 3.136825 18 3.206378 19 3.352655 20 3.490328 21 3.508603 22 3.621768 23 3.803617 24 4.141727 25 4.274712 26 4.345235 27 4.242555 28 4.262047 29 4.378895 30 4.419018 31 4.391497 32 4.489015 33 4.588181 34 4.846862 35 5.069645 36 5.257766 37 5.292695 38 5.307845 39 5.277006 40 5.323614 41 5.377629 42 5.429256 43 5.443411 44 5.472426 45 5.727393 46 6.147055 > ayan= ts(ayan, start=1.611352) > ayan Time Series: Start = 1.611352 End = 46.61135 Frequency = 1 lnrpe [1,] 1.611352 [2,] 1.619602 [3,] 1.599889 [4,] 1.645955 [5,] 1.723777 [6,] 1.830606 [7,] 2.034751 [8,] 2.112377 [9,] 2.095051 [10,] 2.046823 [11,] 2.276628 [12,] 2.543865 [13,] 2.619426 [14,] 2.717786 [15,] 2.874537 [16,] 2.923224 [17,] 3.136825 [18,] 3.206378 [19,] 3.352655 [20,] 3.490328 [21,] 3.508603 [22,] 3.621768 [23,] 3.803617 [24,] 4.141727 [25,] 4.274712 [26,] 4.345235 [27,] 4.242555 [28,] 4.262047 [29,] 4.378895 [30,] 4.419018 [31,] 4.391497 [32,] 4.489015 [33,] 4.588181 [34,] 4.846862 [35,] 5.069645 [36,] 5.257766 [37,] 5.292695 [38,] 5.307845 [39,] 5.277006 [40,] 5.323614 [41,] 5.377629 [42,] 5.429256 [43,] 5.443411 [44,] 5.472426 [45,] 5.727393 [46,] 6.147055 > bp.ayan <- breakpoints(ayan ~ 1) > summary (bp.ayan) Optimal (m+1)-segment partition: Call: breakpoints.formula(formula = ayan ~ 1) Breakpoints at observation number: m = 1 22 m = 2 16 33 m = 3 11 22 34 m = 4 10 16 23 34 m = 5 10 16 23 33 40 m = 6 6 12 18 24 33 40 Corresponding to breakdates: m = 1 22.611352 m = 2 16.611352 33.611352 m = 3 11.611352 22.611352 34.611352 m = 4 10.611352 16.611352 23.611352 34.611352 m = 5 10.611352 16.611352 23.611352 33.611352 40.611352 m = 6 6.611352 12.611352 18.611352 24.611352 33.611352 40.611352 Fit: m 0 1 2 3 4 5 RSS 85.184802 18.716087 8.291525 3.576609 2.244549 1.809104 BIC 166.543984 104.491043 74.697447 43.677063 29.902475 27.638800 m 6 RSS 1.617595 BIC 30.149073 > ci.ayan <- confint(bp.ayan) > ci.ayan Confidence intervals for breakpoints of optimal 6-segment partition: Call: confint.breakpointsfull(object = bp.ayan) Breakpoints at observation number: 2.5 % breakpoints 97.5 % 1 9 10 11 2 15 16 17 3 22 23 24 4 32 33 34 5 34 40 42 Corresponding to breakdates: 2.5 % breakpoints 97.5 % 1 9.611352 10.61135 11.61135 2 15.611352 16.61135 17.61135 3 22.611352 23.61135 24.61135 4 32.611352 33.61135 34.61135 5 34.611352 40.61135 42.61135 > lines(ci.ayan) Error in int_abline(a = a, b = b, h = h, v = v, untf = untf, ...) : plot.new has not been called yet > plot (ayan) > ayan <- read.table("ayan.txt", header=T) > ayan= ts(ayan, start=1.611352) > bp.ayan <- breakpoints(ayan ~ 1) > summary (bp.ayan) Optimal (m+1)-segment partition: Call: breakpoints.formula(formula = ayan ~ 1) Breakpoints at observation number: m = 1 22 m = 2 16 33 m = 3 11 22 34 m = 4 10 16 23 34 m = 5 10 16 23 33 40 m = 6 6 12 18 24 33 40 Corresponding to breakdates: m = 1 22.611352 m = 2 16.611352 33.611352 m = 3 11.611352 22.611352 34.611352 m = 4 10.611352 16.611352 23.611352 34.611352 m = 5 10.611352 16.611352 23.611352 33.611352 40.611352 m = 6 6.611352 12.611352 18.611352 24.611352 33.611352 40.611352 Fit: m 0 1 2 3 4 5 RSS 85.184802 18.716087 8.291525 3.576609 2.244549 1.809104 BIC 166.543984 104.491043 74.697447 43.677063 29.902475 27.638800 m 6 RSS 1.617595 BIC 30.149073 > ci.ayan <- confint(bp.ayan) > ci.ayan Confidence intervals for breakpoints of optimal 6-segment partition: Call: confint.breakpointsfull(object = bp.ayan) Breakpoints at observation number: 2.5 % breakpoints 97.5 % 1 9 10 11 2 15 16 17 3 22 23 24 4 32 33 34 5 34 40 42 Corresponding to breakdates: 2.5 % breakpoints 97.5 % 1 9.611352 10.61135 11.61135 2 15.611352 16.61135 17.61135 3 22.611352 23.61135 24.61135 4 32.611352 33.61135 34.61135 5 34.611352 40.61135 42.61135 > -------------- next part -------------- lnrpe 1.6113515 1.619601724 1.599889264 1.645954835 1.723777317 1.830606002 2.034751407 2.112377045 2.095050993 2.046822835 2.276628064 2.543864584 2.619425807 2.717786454 2.874537082 2.923223972 3.136825311 3.206377996 3.352655132 3.49032806 3.508602739 3.621768106 3.803617305 4.141727497 4.27471221 4.34523451 4.242555261 4.262046942 4.378894917 4.419018243 4.391496862 4.489015146 4.588180885 4.846861554 5.069645376 5.257766481 5.292695491 5.307844982 5.277006289 5.323613873 5.377629069 5.429256311 5.443411354 5.47242567 5.727392687 6.147054773