similar to: strucchange Fstats() example

Greetings: Is there an simple way to do dynamic regressions in R? >From what I've seen, one must use arima() and construct the X matrix with lagged values etc. and modify Y as well. Thanks, Bob --------------------------------- [[alternative HTML version deleted]]

Hi, I am new to R. It would be kind if I could get some help on this. I am using R to estimate Fstats but I am getting following error. a3 is annual GDP data from 1951 to 2010. > fs<- Fstats(ecm.model, from=1954, to = 1975,data=a3) Error in Fstats(ecm.model, from = 1954, to = 1975, data = a3) : inadmissable change points: 'from' is larger than 'to' In addition: Warning

Hi, I have recently use the strucchange package in R with a single time series observation. I found it extremely useful in the testing of change points. Now, I am thinking of using the strucchange package with panel data (about 500 firms, with 73 monthly time series observations each). For each firm, I have to conduct the Fstats and breakpoints tests. Based on the test of each firm, I have to

Is it possible to use some form of robust regression with the breakpoints routine so that it is less sensitive to outliers? --Rich Richard Kittler Advanced Micro Devices, Inc. Sunnyvale, CA

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,

Good morning to all, I am encountering a blocking issue when using the function 'breackpoints' from package 'strucchange'. *Context:* I use a data frame, 248 observations of 5 variables, no NA. I compute a linear model, as y~x1+...+x4 x4 is a dummy variable (0 or 1). I want to check this model for structural changes. *Process & issues:* *First, I used function Fstats.* It

Dear all, I'm using the mgcv library by Simon Wood to fit gam models with interactions and I have been reading (and running) the "factor 'by' variable example" given on the gam.models help page (see below, output from the two first models b, and b1). The example explains that both b and b1 fits are similar: "note that the preceding fit (here b) is the same as

Hello, I used the function Fstats (in the package strucchange) and would like to transform the F probability given by Fstats in P value. This transformation can be made while making a plot, but I need to have the numerical P value which are ploted... and I can't find out how to do. Here a is an exemple, to plot the P value. let's take data as a array fs <-fstats(data ~ 1, from = 4,

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'm trying to detect breaks points in various flow time series, they all contains seasonality and trend my question is : i have to remove this seasonality and trend before apply the function breakpoints du package strucchange?? another question, the function breakpoints is similar to de Pettit tests ? or how does it realy works? THANKS!!!! DENISSE -- View this message in context:

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

can you recommend a good manual for R that starts with a data set and gives demonstrations on what can be done using R? I downloadedR Langauage definition and An introduction to R but haven't found them overly useful. I'd really like to be able to follow some tutorials using a dataset or many datasets. The datasets I have available on R are Data sets in package 'datasets':

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 a new user to R. I am using strucchange to generate breakpoints: -------------------------------------------------------------------------------------- > res <- gbreakpoints(GDP.new ~ 1,data=a,h=2,breaks=5) > print(res) Optimal 6-segment partition for `lm' fit: Call: gbreakpoints(formula = GDP.new ~ 1, data = a, h = 2, breaks = 5) Breakpoints at observation number:

Dear R users, I'm trying to use the "strucchange" package to determine structural breaks in an ARFIMA model. Unfortunately I'm not so familiar with this topic (and worse, I'm a beginner in R), so I don't know exactly how to specify my model so that the "Fstats","sctest" and "breakpoint" functions to recognize it and to calculate the

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

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

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

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

Dear R Users, I am attempting to use the strucchange package but get an error which is difficult to decipher. I get the following error with breakpoints: > bp<-breakpoints(regr[,1]~regr[,2]+regr[,3]) Error in my.RSS.table[as.character(i), 3:4] <- c(pot.index[opt], break.RSS[opt]) : nothing to replace with I was wondering if anyone has seen this issue before and off the top of