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TSsmoothing

0.1.0

Trend Estimation of Univariate and Bivariate Time Series with Controlled Smoothness

0packages depend
2.1Kdownloads / year
test coverage
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Overview

About
Maintained by L. Leticia Ramirez-RamirezFirst published 2019-07-151 releasesCRAN page ↗

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.

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1NOTE12OK
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Tests · ratio 0.00
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Check history
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

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References docs
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Dependencies

Declared dependencies
2 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5.0
Imports (4)
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
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Code & Tests

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People (3)
Maintainer (1)
Author, Maintainer
Authors (3)
Package Timeline

1 release. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 0.1.0Latest
    2026-03-10 · current release
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2019-07-15
Total releases
1 / 7 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5.0
Bundled data
372 KB / 3 files
Download size
383 KB
Installed size
not tracked yet
With dependencies
not tracked yet
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