similar to: STRUCCHANGE DETECTING BREAKPOINTS IN A TIME SERIES

hi i try to do a graph of a time series which shows in red the values > -0.05, in blue the values >0.05 and in white the values between -0.05 and 0.05 for un exemple :http://www.appinsys.com/globalwarming/enso.htm thanks !!!!! denisse -- View this message in context: http://r.789695.n4.nabble.com/how-to-do-a-graph-with-tree-different-colors-tp4635206.html Sent from the R help mailing

Hello, I have done some research about breakpoints (I am not a statistician) and I found out about the breakpoint, strucchange and segmented packages in R allowing to find breakpoints assuming linear model. However, I would like to fit a periodic time series with a non linear (periodic) model, and I was wondering how I could find breakpoints for this model in R. Is it even possible ? My model

Can anyone please tell me how to get the r-squared output from a piecewise (segmented) regression using the strucchange package? Here is the R code I have tried thus far. library(lmtest) library(strucchange) data <- ts(c(rnorm(30), runif(30)), frequency = 12, start = c(2005, 01)) bpts <- breakpoints(data ~ 1) print(bpts) summary(bpts) coeftest(bpts) [[alternative HTML version

If I try the breakpoints() function (strucchange package) with a minimum segment size = the number of regressors, there appears the following error message: "minimum segment size must be greater than the number of regressors" According to the documentation: "breakpoints implements the algorithm described in Bai & Perron (2003) for simultaneous estimation of multiple

Dear R-Team, Am I right supposing that the "breakpoints()" function in the strucchange package is an implementation of the pure structural change model proposed by Bai and Perron (1997, 2003)? My question relates to a partial structural change model that Bai and Perron formulate in their 2003 paper, e.g. formulated as y = x' beta + z' delta_j + epsilon, where beta and delta

Hola! I am using package strucchange, and encounters the following: > bp <- breakpoints(diesel90 ~ regress -1, h=NULL) Error in La.chol2inv(x, size) : element (14, 14) is zero, so the inverse cannot be computed The obvious problems have been checked, that is, the model matrix is of full rank. What can be causing this? I can send some data if that can be of help. Kjetil Halvorsen

Hello, we want to identify breakpoints (different phases) in environmental data, algae cell counts of three years with intervals between 7 and 30 days (N=40). We found that breakpoints(cells ~1) works great and identifies 5 very good breaks, however we are uncertain about these, because the data are unequally spaced. Is there a way to include the information about the measurement intervals,

Hi, I am new to R. I am using strucchange to get the breakpoints in time series dataset. So the problem I am facing is: I want to link the result generated by the breakpoints to further analysis (for eg. generating volatility for each group). The result is in following form: --------------------------------------- > res <- gbreakpoints(GDP.new ~ 1,data=a,h=2,breaks=6) > res

Hi, I am trying to a strucutural change analysis on a certain data set. Attached here, with variable name "xcd" http://old.nabble.com/file/p26226190/xcd.rda xcd.rda Am using the following command: bp.inrz<-breakpoints(INR~SPX+WPI,data=xcd,h=26) But keep on getting this error whatever variables i put in on the x side as regressors: Error in chol2inv(qr.R(qr(X))) : element (3,

Hi to all, I am trying to run breakpoints() on a fairly large sample (>10.000 observations). The process is very slow, any idea on how to speed this up? I have tried the hpc="foreach" parameter, but this didn't work at all when I tried to run it on a smaller sample. breakpoints(x ~ x.l1 + x.l2 + X.l3 + x.l4 + x.l5 + x.l6 + x.l7 + x.l8 + y.l1 + y.l2 + y.l3 + y.l4 + y.l5 + y.l6

Hi everybody. I'm using BFAST program and I have some data to be analized (named "META.csv" for example). When I call BFAST in the following way: meta <- read.csv("C:/META.csv") meta.ts<-ts(meta, frequency=12, start = c(2005,9)) dis<-frequency(meta.ts) / length(meta.ts) meta.sc<-bfast(meta.ts, h=dis, max.iter=1) meta.sc$output The last statement has the

hello R-world, according to the strucchange package .pdf, "all procedures in this package are concerned with testing or assessing deviations from stability in the classical linear regression model." i'd like to test/assess deviations from stability in the Poisson model. is there a way to modify the strucchange package to suit my purposes, or should i use be using another

Greetings, I'm complety new to "R" and have a question. I've read through a couple of manuals but I'm having a problem with getting something run properly. I'd like to attempt to use the "strucchange" package with some sample data however I'm having trouble understanding the proper syntax of the commands from which to do so. I basically want to take

Greetings - Am hoping to use the strucchange package to look for structural breaks in some messy regression data. A series of preliminary analyses indicate that BLUE for these data will involve some weighting the data (estimates of a particular population parameter) by a function of the variance of the estimate (say, inverse of the variance). While I've gone through the docs for

When I run the code below on Macintosh and Windows, the plot comes out fine. However, on Linux, the png generated is invalid from R console, and loading strucchange crashes rkward. Is this a known issue on Linux and, if so, is there a workaround? Many thanks! require(strucchange) data("RealInt") bp.ri <- breakpoints(RealInt~1, h=15) summary(bp.ri) fac.ri <- breakfactor(bp.ri,

Hi Achim, I'd like to try to run the strucchange package on R. However, it seems that the package can only run on systems running Debian and not Windows XP. Is this true? Or is there a windows version? I downloaded the strucchange file but they seem to have the dot deb extension and seem to be designed to run with Debian. If there is a windows version, could you please let me know how to

Hello, I am just studying the following example from vignette: strucchange-intro, contineousely ending up in an error. This is the given code: 1. library(strucchange) 2. data(USIncExp) 3. if (!"package:stats" %in% search()) library(ts) 4. USIncExp2 <- window(USIncExp, start = c(1985, 12)) A.Modelling: coint.res <- residuals(lm(expenditure ~ income, data = USIncExp2))

Hello, to understand better how efpFunctional works, I'm trying to construct my own functionals. But concerning already existing functionals I have some questions. With maxBB it is clear: functional = list(comp = function(x) max(abs(x)), time = max), with rangeBB: functional = list(time = function(x) max(x)-min(x), comp = max), with meanL2BB, if I understood correctly: functional =

I want to apply Nyblom-Hansen test with the strucchange package, but I don't know how is the correct way and what is the difference between the following two approaches (leeding to different results): data("longley") # 1. Approach: sctest(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley, type = "Nyblom-Hansen") #results in: # Score-based CUSUM

Hello, Im using strucchange package in R software in order to apply Bai and Peron (1998, 2003) structural break tests to a set of n=1671 observations with a constant term (no AR terms). For that purpose I have read several papers, for instance Validating Multiple Structural Change Models An Extended Case Study, in which its aim is to replicate the results from Bai and Perron (2003) in R