demo/shiny_TS/README.md
In AlexisMayer/toolbox:
Simulation tools
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Application allow you to fully understand your own time-series dataset throw a shiny interactive interface
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Several tools are proposed. First, you can drop your dataset which contain time-series. Then, you can decompose in trend, seasonal and residual signals. Finaly, it will allow you to create a model in order to determine the driving force between your variables. Simulation is the last tool proposed. You can build your own senario such as a ponctual variation on a variable or a long-term trend variation. \
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- Test validation of the input dataset
- Decomposition \& Stationarity test
- VAR model
- Simulation \& Prevision
AlexisMayer/toolbox documentation built on Aug. 25, 2020, 3:56 p.m.
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Simulation tools
\Application allow you to fully understand your own time-series dataset throw a shiny interactive interface
\Several tools are proposed. First, you can drop your dataset which contain time-series. Then, you can decompose in trend, seasonal and residual signals. Finaly, it will allow you to create a model in order to determine the driving force between your variables. Simulation is the last tool proposed. You can build your own senario such as a ponctual variation on a variable or a long-term trend variation. \
\
- Test validation of the input dataset
- Decomposition \& Stationarity test
- VAR model
- Simulation \& Prevision
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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