Description Usage Arguments Value Examples
all in one function of iterated HP-filter
1 |
x |
the data you want to conduct HP-filter |
lambda |
the turning parameter |
iter |
logical parameter, TRUE is to conduct iterated HP-filter, FALSE is not |
test_type |
the type for creterion |
sig_p |
significant p-value |
Max_Iter |
maximum iterated time |
cycle component, iterated number, p-value .
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | lam <- 100 # tuning parameter for the annaul data
# raw HP filter
bx_HP <- BoostedHP(x, lambda = lam, iter= FALSE)$trend
# by BIC
bx_BIC <- BoostedHP(IRE, lambda = lam, iter= TRUE, test_type = "BIC")
# by ADF
bx_ADF <- BoostedHP(IRE, lambda = lam, iter= TRUE, test_type = "adf", sig_p = 0.050)
# summarize the outcome
outcome <- cbind(IRE, bx_HP$trend, bx_BIC$trend, bx_ADF$trend)
matplot(outcome, type = "l", ylab = "", lwd = rep(2,4))
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