mocatfrio / timeseries

A documentation for timeseries course 2020

Time Series Analysis

Documentation of Time Series Analysis Course 2020 by

• 05111950010029 - Yolla Faradhilla
• 05111950010040 - Hafara Firdausi

Assignments

1. ARIMA - Paper Review
2. RNN for Timeseries
   • Forecasting Price of Chicken
3. LSTM for Timeseries
   • Predicting Eye Movements
   • Forecasting Electrocardiogram Activity
4. GSTAR
   • Predicting Temperature in Surabaya

Tools

• R
• RStudio (maybe you use this)
• Jupyter Notebook (I prefer this!)

Configure Jupyter Notebook to work with R on a Mac

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 💖

1. Open your terminal, install libgit2 using brew

   $ brew install libgit2

2. Open R within terminal

   $ R

3. Install these R libraries

   > install.packages(c(
     'repr',
     'IRdisplay',
     'evaluate',
     'crayon',
     'pbdZMQ',
     'devtools',
     'uuid',
     'digest',
     'git2r'
     ), dependencies = TRUE)

4. Install IRkernel package from Github using devtools::install_github

   > devtools::install_github('IRkernel/IRkernel')

5. Install the Interactive R kernel system-wide

    > IRkernel::installspec(user = FALSE)

6. Done! Open your Jupyter Notebook and let's have fun!

   $ jupyter notebook

   

References

• N.D. Lewis - Neural Networks for Time Series Forecasting with R (2017)
• William W.S.Wei - Time Series Analysis (2006)