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Project for local linear regression for use with metabolic time-series data
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Local Linear Regression for Estimating Monotonic Biological Rates in R (LoLinR)

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We introduce the LoLinR package, which provides tools to implement local linear regression techniques for estimating monotonic rates from time-series or trace data in a statistically robust and reproducible fashion. The methods are a modification of traditional Loess regression techniques built around the wrapper function rankLocReg().

See the package documentation for LoLinR through our online html_vignette. You can also find the final version of the peer reviewed article describing the methods here.

Citing LoLinR

When using LoLinR for your research, please cite:

Olito, C., C.R. White, D.J. Marshall, and D.R. Barneche. 2017. Estimating monotonic rates from biological data using local linear regression. Journal of Experimental Biology. DOI: 10.1242/jeb.148775.


The LoLinR package can be installed from github using the devtools package using devtools::install_github.

If you do not yet have devtools, install with install.packages("devtools").

Then install LoLinR using the following:

LoLinR does not currently have any functional dependencies on other packages. However, it loads lmtest for the purposes of unit testing.

Contact & bug reporting

LoLinR is in the final stages of development, and will continue to get frequent updates until this process is finished. We currently need beta testing, and encourage users to test the package and report any bugs and/or problems by opening an issue on the LoLinR github webpage here. If you would like to report a bug/issue, and do not have a github account (and don't want to get one), please send a brief email detailing the problem you encountered to

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