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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>.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 TSsmoothing_0.1.0.tar.gz 425.8 KiB
0.1.0 rolling linux/noble R-4.5 TSsmoothing_0.1.0.tar.gz 425.6 KiB
0.1.0 rolling source/ R- TSsmoothing_0.1.0.tar.gz 381.9 KiB
0.1.0 latest linux/jammy R-4.5 TSsmoothing_0.1.0.tar.gz 425.8 KiB
0.1.0 latest linux/noble R-4.5 TSsmoothing_0.1.0.tar.gz 425.6 KiB
0.1.0 latest source/ R- TSsmoothing_0.1.0.tar.gz 381.9 KiB
0.1.0 2026-04-26 source/ R- TSsmoothing_0.1.0.tar.gz 381.9 KiB
0.1.0 2026-04-23 source/ R- TSsmoothing_0.1.0.tar.gz 381.9 KiB
0.1.0 2026-04-09 windows/windows R-4.5 TSsmoothing_0.1.0.zip 429.1 KiB
0.1.0 2025-04-20 source/ R- TSsmoothing_0.1.0.tar.gz 381.9 KiB

Dependencies (latest)

Imports