Time Series analysis concepts using examples in r. Multiple data sets were used to demonstrate reading in data, filtering, date conversion, plotting (autoplot, gg_season, gg_subseries, GGalley), seasonality, cross correlation, autocorrelation, ACF, lag, white noise etc.
Packages: fpp3, readr
Data Preprocessing:
- tsibble objects
- Data: PBS (tsibble object) containing monthly data on Australia medicare prescription data
- Filtering (Month, Concession, Type, Cost)
- Summarise (all costs in a given month)
- Mutate to create a new cost column
- Date conversion
- Tsibble object Date conversion
- Airport Data
- Autoplot of Cost (Antidiabetic drug sales)
- Checking for seasonality
- Seasonal subseries plot
- Demand per day, week, year etc.
- "Australian domestic holiday nights" Time series plots
- autoplot, gg_season, gg_subseries
- Cross Correlation: "Half-hourly electricity demand: Victoria, Australia"
- Demand, temperature
- GGally
- Auto-correlation - checking for lag one time period ago
- (ACF) auto correlation function
- White Noise
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