The smoots Package in R for Semiparametric Modeling of Trend Stationary Time Series

This paper is an introduction to the new package in R called [smoots](https://CRAN.R-project.org/package=smoots) (smoothing time series), developed for data-driven local polynomial smoothing of trend-stationary series. Functions estimation first and second derivatives trend are also built-in. It applied monthly changes global temperature. The quarterly US-GDP series shows that this can be well a semiparametric multiplicative component model non-negative via log-transformation. Furthermore, we introduced Log-GARCH Log-ACD model, which easily estimated by smoots package. Of course, applies suitable from any other research area. provides useful tool teaching analysis, because many practical follow additive or model.