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(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley), functional = meanL2BB) #results in: # M-fluctuation test # #data: gefp(Employed ~ Year + GNP.deflator + GNP + Armed.Forces, data = longley) #f(efp) = 0.8165, p-value = 0.3924 I could not find any examples or further remarks of the first approach with sctest(..., type = "Nyblom-Hansen"). Maybe the first approach is unlike the second no joint test for all coefficients? Thank you in advance for your help! -- View this message in context: http://r.789695.n4.nabble.com/strucchange-Nyblom-Hansen-Test-tp3887208p3887208.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.