Thank you very much for the answer. If I take Poisson model and follow "Generalized M-fluctuation tests for parameter instability", A. Zeileis and K. Hornik, Statistica Neerlandica (2007) Vol. 61, N. 4, p. 500-501 (section 4.3):
data("Boston") n <- 506; my.X <- as.matrix(cbind(1, Boston["crim"], Boston["age"])); my.model <- glm(tax ~ crim + age, family = poisson, data = Boston); my.psi <- estfun(my.model); my.mu <- fitted(my.model); J <- sum(my.mu*my.X%*%t(my.X))/n; my.process <- apply(as.matrix(my.psi), 2, cumsum)/sqrt(J*n); gprocess <- gefp(tax ~ crim + age, family = poisson, data=Boston); then my.process and gprocess$process have to be the same? Best regards, Julia -- View this message in context: http://r.789695.n4.nabble.com/gefp-boundaries-tp3872529p3878886.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.