# Class Proposed Schedule

The proposed schedule below is subject to change. My initial plan is to cover all the material listed here but I might modify it if extra time is needed for some particular topics. I will update this table as needed during the semester.

Lecture | Module | Date | Topic | Homework |
---|---|---|---|---|

L1 | M1 | Jan 11 | Introductions and Course Overview | Join Slack Workspace and A01 |

L2 | M1 | Jan 16 | Intro to Time Series Analysis, Intro to R and RStudio, Github, R Markdown | A01 |

L3 | M2 | Jan 18 | TSA Applications in Energy and Environment Autocovariance and autocorrelation function R file “M2_ACF_PACF.Rmd” |
Run “M2_ImportingData_CSV_XLSX.Rmd” and A02 |

L4 | M2 | Jan 23 | Partial autocorrelation function ACF and PACF in R File “M2_ACF_PACF_Complete.Rmd” Temperature Example in Exccel |
A02 |

L5 | M3 | Jan 25 | Trend Component Estimation | A03 |

L6 | M3 | Jan 30 | Seasonal Component Estimation | A03 |

L7 | M3 | Feb 1 | Trend and Seasonal component estimation in R “M3_TrendSeasonality_AfterClassFeb1” |
A03 |

L8 | M3 | Feb 6 | A3 solution Stochastic vs Deterministic Trend |
A04 |

L9 | M3 | Feb 8 | Stationarity Tests- Mann Kendall Spearman Augmented Dickey Fuller R file: “M3_TrendSeasonality_Complete.Rmd” |
A04 |

L10 | M4 | Feb 13 | A4 solution Outlier types and detection How to handle missing data |
A05 |

L11 | M4 | Feb 15 | Outliers in R files: “M4_MissingDataAndOutliers_Example1.Rmd” “M4_MissingDataAndOutliers_Example2.Rmd” Intro to the Traditional Box Jenkins Models - ARIMA family Stationary Models: AR and MA process |
A05 |

L12 | M5 | Feb 20 | A5 solution AR and MA models |
A06 |

L13 | M5 | Feb 22 | ARIMA(p,d,q) Models Fitting ARIMA Models in R R file: “M5_ARIMAModels_AfterClassFeb22.Rmd” |
A06 |

L14 | M6 | Feb 27 | Seasonal ARIMA and Periodic ARMA Models R file: “M5_ARIMAModels_ClassFeb27.Rmd” |
A07 |

L15 | M6 | Feb 29 | A6 solution Finish SARIMA in R R file: “M6_SeasonalARIMA_AfterClassFeb29.Rmd” |
A07 |

L16 | M7 | Mar 5 | Intro to Forecasting Averaging Techniques Forecasting with ARIMA Models |
A07 |

L17 | M7 | Mar 7 | Forecasting in R R file: “M7_Intro_Forecasting_AfterClassMar7.Rmd” |
A07 |

- | - | Mar 12 | Spring break no class |
- |

- | - | Mar 14 | Spring break no class |
- |

L18 | M8 | Mar 19 | Model Diagnostics Residual Analysis and Model Selection Go over Final Project folder |
A09 - Part I: Project Proposal (2-3 slides) |

L18 | M8 | Mar 21 | A07 solution Model Performance in R R file: “M8_ModelPerformance_ClassMar21.Rmd” Go over Forecasting Competition |
A08 - part I |

L20 | M10 | Mar 26 | Advanced Forecasting Models Forecasting higher frequency time series R file: “M10_AdvancedForecastingModels.Rmd” |
A08 - part I |

L21 | M10 | Mar 28 | Advanced Forecasting Models in R Bayesian Statistics |
A08 - part II |

L22 | M9 | Apr 2 | State-Space Models R file: “M9_StateSpaceModels.Rmd” |
A08 - part II |

L23 | M9 | Apr 4 | Adding exogenous regressors in R Scenario Generation in R R file: “M10_ScenatioGeneration_ClassApr4.Rmd” |
Work on project/competition |

L22 | M11 | Apr 9 | Scenario Generation with ARIMA in R R file: “M10_ScenatioGeneration_Complete.Rmd” Course Recap Course Evaluations |
Work on project/competition |

L23 | - | Apr 11 | MEM Symposium - no class |
Work on project/competition |

L24 | - | Apr 16 | Final Project Presentations Presentation Schedule |
Work on project/competition |