#fit a LSTAR model. Note 'maxit': slow convergence
mod.lstar <- lstar(log10(lynx), m=2, mTh=c(0,1), control=list(maxit=3000))
mod.lstar
#fit a LSTAR model without a constant in both regimes.
mod.lstar2 <- lstar(log10(lynx), m=1, include="none")
mod.lstar2
#Note in example below that the initial grid search seems to be to narrow.
# Extend it, and evaluate more values (slow!):
controls <- list(gammaInt=c(1,2000), nGamma=50)
mod.lstar3 <- lstar(log10(lynx), m=1, include="none", starting.control=controls)
mod.lstar3
# a few methods for lstar:
summary(mod.lstar)
residuals(mod.lstar)
AIC(mod.lstar)
BIC(mod.lstar)
plot(mod.lstar)
predict(mod.lstar, n.ahead=5)
更多的看这个文档：http://cran.r-project.org/web/packages/tsDyn/tsDyn.pdf
扫码加好友，拉您进群
全部版块
我的主页
收藏
