Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness R package TSsmoothing version 0.1.0 It performs the smoothing approach provided by penalized least squares for univariate and bivariate time series, as proposed by Guerrero (2007) and Gerrero et al. (2017). This allows to estimate the time series trend by controlling the amount of resulting (joint) smoothness. --- Guerrero, V.M (2007) <DOI:10.1016/j.spl.2007.03.006>. Guerrero, V.M; Islas-Camargo, A. and Ramirez-Ramirez, L.L. (2017) <DOI:10.1080/03610926.2015.1133826>. Software Depends: R (>= 3.5.0) Imports: ggplot2(>= 3.2.0), MASS (>= 7.3.0), gridExtra (>= 2.3.0), Matrix (>= 1.2.0) L. Leticia Ramirez-Ramirez <leticia.ramirez@cimat.mx> Comprehensive R Archive Network (CRAN) L. Leticia Ramirez-Ramirez [aut, cre], Alejandro Islas-Camargo [aut], Victor M. Guerrero [aut] GPL-3 2019-07-15 application/tgz https://CRAN.R-project.org/package=TSsmoothing doi:10.32614/CRAN.package.TSsmoothing