knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(fastTS) library(magrittr) # for pipe
data("LakeHuron") fit_LH <- fastTS(LakeHuron) fit_LH coef(fit_LH)
If you have a univariate time series with suspected trend, such as the EuStockMarkets data set,
data("EuStockMarkets") X <- as.numeric(time(EuStockMarkets)) X_sp <- splines::bs(X-min(X), df = 9) fit_stock <- fastTS(log(EuStockMarkets[,1]), n_lags_max = 400, X = X_sp, w_exo = "unpenalized") fit_stock tail(coef(fit_stock), 11) # insert plot?
data("nottem") fit_nt <- fastTS(nottem, n_lags_max = 24) fit_nt coef(fit_nt)
data("UKDriverDeaths") fit_ukdd <- fastTS(UKDriverDeaths, n_lags_max = 24) fit_ukdd coef(fit_ukdd)
data("sunspot.month") fit_ssm <- fastTS(sunspot.month) fit_ssm
Model summaries
summary(fit_ssm)
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