mbte-package: Model-based trend estimation
In mkerschbaumer/mbte: Model-based trend estimation
Description
This package is inspired by the
Managing many
models-talk by Hadley Wickham. The intuition is to fit arbitrary models
to a signal. Those models are used to generate predictions. An (error)-metric
gets computed, based on the predicted and the original value of the signal.
Using dplyr, relevant
measurement-variables can be kept and investigated further by filtering the
metric-results. The results can be visualized using
ggplot2.
Details
The general workflow and the way the different components of this package
interact, can be seen in the introduction vignette.
mkerschbaumer/mbte documentation built on May 5, 2019, 11:01 p.m.
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Description
This package is inspired by the Managing many models-talk by Hadley Wickham. The intuition is to fit arbitrary models to a signal. Those models are used to generate predictions. An (error)-metric gets computed, based on the predicted and the original value of the signal. Using dplyr, relevant measurement-variables can be kept and investigated further by filtering the metric-results. The results can be visualized using ggplot2.
Details
The general workflow and the way the different components of this package interact, can be seen in the introduction vignette.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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