Documentation of Time Series Analysis Course 2020 by
- 05111950010029 - Yolla Faradhilla
- 05111950010040 - Hafara Firdausi
- ARIMA - Paper Review
- RNN for Timeseries
- LSTM for Timeseries
- GSTAR
- R
- RStudio (maybe you use this)
- Jupyter Notebook (I prefer this!)
I'm totally new in the R language and not comfortable using RStudio. So, I looked for other alternatives that could make me having fun with R. And yeah, I end up using Jupyter Notebook right now! xoxo, thanks jupyter ๐
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Open your terminal, install
libgit2
using brew$ brew install libgit2
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Open R within terminal
$ R
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Install these R libraries
> install.packages(c( 'repr', 'IRdisplay', 'evaluate', 'crayon', 'pbdZMQ', 'devtools', 'uuid', 'digest', 'git2r' ), dependencies = TRUE)
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Install IRkernel package from Github using
devtools::install_github
> devtools::install_github('IRkernel/IRkernel')
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Install the Interactive R kernel system-wide
> IRkernel::installspec(user = FALSE)
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Done! Open your Jupyter Notebook and let's have fun!
$ jupyter notebook
- N.D. Lewis - Neural Networks for Time Series Forecasting with R (2017)
- William W.S.Wei - Time Series Analysis (2006)