search for: sctest

...generics from a foreign package (without namespace), defining a S3 method in a package _with_ namespace and the `cleanEx()' function which is automatically generated and executed before examples are run by R CMD check. To be more precise. Package `strucchange' defines a S3 generic sctest <- function(x, ...) UseMethod("sctest") and the development version of `party' defines sctest.mob <- function(x, node = NULL, ...) { ... which is exported in party's namespace S3method(sctest, mob) Creating a `mob' object and running `sctest'...

...ssion using lm function:   > reg1 <- lm (a b+c+d, data = database1)   Then I try to perform the Chow (1960) test (structural change test) on my regression. I know the breakpoint date. I try the following code like it is described in the “Examples” section of the “strucchange” package :   > sctest(reg1, data = database1, type = "Chow",  point = 20, asymptotic = FALSE)   Unfortunately, this does not work and I have the following error message:   Error in UseMethod("sctest") : No applied method for "sctest".   I guess that I should compute fs statistics first (Fis...

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 test with mean L2 norm # #data: Employed ~ Year + GNP.deflator + GNP + Armed.Forces #f(efp) = 0.8916, p-value = 0.4395 #2. Approach: sctest(gefp(Employe...

Hullo, I am attempting to use collections in order to distribute ssh keys across (soon) many hosts but I am hitting some trouble (the recipe I am using is at the end of this email). Namely it looks like sshkeys resources are not marked as exported in the sqlite db. I.e. if I do: sqlite3 clientconfigs.sqlite3 SQLite version 3.3.5 Enter ".help" for instructions sqlite> select *

...(tax_ivreg) ## after estimating it, something weird happened with the several tests in package "strucchange". For example: cusum <- efp(l_y ~ l_x2 + l_x1+ dl_y | lag(l_x2, -1)+lag(l_x2, -2)+ lag(l_x1, -1)+lag(l_x1, -2)+lag(l_y, -1)+lag(l_y, -2), data=tax1, type="OLS-CUSUM") sctest(cusum) plot(cusum) coef(cusum, breaks=2) ## And: cusum <- efp(tax_ivreg, data=tax1, type="OLS-CUSUM") sctest(cusum) plot(cusum) coef(cusum, breaks=2) ## 1. The plot of the two above were very different and ## 2. When I ask for the breaks, instead of the dates, it returned me a line...

...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 potentially breakpoints. Could anyone give me a sugestion? I tried, however, (following the example specified in R Help) the functions: fs.x <- Fstats(x ~ 1)) sctest(fs.x) plot(fs.x) breakpoints(fs.x) But I unders...

...t;- c("MS", "time", "pred", "class") df$time[df$time > 6] <- 6 surv <- Surv(as.numeric(as.vector(df$time)), as.numeric(as.vector(df$class))) dfPval <- summary(coxph(Surv(as.numeric(as.vector(df$time)), as.numeric(as.vector(df$class))) ~ pred, df))$sctest par(mfrow = c(2,2)) plot(survfit(surv ~ df$pred), col=c("red","green"), ylab = "percentage of survival", xlab = "survival years") plot(survfit(surv ~ df$pred), col=c("red","green"), lwd = 8, ylab = "percentage of survival", xlab...

...u = double(nvar), imat= double(nvar*nvar), loglik=double(2), flag=integer(1), double(2*n + 2*nvar*nvar + 3*nvar), as.double(control$eps), as.double(control$toler.chol), sctest=as.double(method=="efron") ,PACKAGE="survival") produces R> coxfit$coef [1] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN because (?) R> summary(x[,1]) Min. 1st Qu. Median Mean 3rd Qu. Max. 2.378e-01 8.758e+00 5...

...d, and Score test p-values from the coxph.object, as well as the hazard ratio as follows: formula.obj = Surv(days, status) ~ type coxph.model = coxph(formula.obj, df) fit = summary(coxph.model) hazard.ratio = fit$conf.int[1] lower95 = fit$conf.int[3] upper95 = fit$conf.int[4] logrank.p.value = fit$sctest[3] wald.p.value = fit$waldtest[3] lr.p.value = fit$logtest[3] I had intended to report logrank P values with the hazard ratio and CI obtained from this function. In one case the P was 0.04 yet the CI crossed one, which confused me, and certainly will raise questions by reviewers. In retrospect I...

...offset)), newstrat, means = double(nvar), coef= as.double(beta), u = double(nvar), imat= double(nvar*nvar), loglik=double(2), flag=integer(1), double(2*nvar*nvar +nvar*4 + n), integer(2*n), as.double(control$eps), as.double(control$toler.chol), sctest=double(1), as.integer(length(debugfile)), as.character(debugfile), as.integer(1), # dumb mode PACKAGE="survivalrds" ) - r$loglik[2] } r <- optim(init, agfitfn, ...) return(r) All of this is in the body...

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)

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

Does anyone know where I can get R code for plotting the Brown , Durbin and Evans cumsum procedure ( 1975 ) ? I wrote my own code but I am a little worried that my confiodence bands may not be correct ( I find the formula in the original paper confusing and S+Finmetrics has a formula but that formula implies that there should be 4 lines as far as I can tell ) so I would like to see someone

Full_Name: Jerome Asselin Version: 1.6.1 OS: RedHat Linux 7.2 Submission from: (NULL) (142.103.173.179) Hello, I get a segmentation fault when I run the following code. I wouldn't expect meaningful results because my response variable contains only missing values. However, I would expect something like a regular error (not a segmentation fault). library(survival) data <-

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

...he following code ## Nile data with one breakpoint: the annual flows drop in 1898 ## because the first Ashwan dam was built data("Nile") plot(Nile) ## test the null hypothesis that the annual flow remains constant ## over the years fs.nile <- Fstats(Nile ~ 1) plot(fs.nile, alpha=0.05) sctest(fs.nile) ## visualize the breakpoint implied by the argmax of the F statistics plot(Nile) lines(breakpoints(fs.nile)) In the second example, the authors state the presence of "at least" two breakpoints. When plotting the F-statistics using the following code, we see indeed two peaks in...

Hi, I want to fit multiple cox models using the coxph() function. To do this, I use a for-loop and save the relevant results in a separate matrix. In the example below, only two models are fitted (my actual matrix has many more columns), one gives a warning message, while the other does not. Right now, I see all the warning message(s) after the for-loop is completed but have no idea which model

Hi, does anybody know of a nice test to detect trend turning points in time series? Possibly with reference? Thanks, joerg