TSsmoothing: Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness

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>.

Getting started

Package details

AuthorL. Leticia Ramirez-Ramirez [aut, cre], Alejandro Islas-Camargo [aut], Victor M. Guerrero [aut]
MaintainerL. Leticia Ramirez-Ramirez <leticia.ramirez@cimat.mx>
LicenseGPL-3
Version0.1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("TSsmoothing")

Try the TSsmoothing package in your browser

Any scripts or data that you put into this service are public.

TSsmoothing documentation built on July 15, 2019, 5:01 p.m.