Forecasting Seasonal Time Series in R
Traditional forecasting methods require stationary data to make a valid forecast. In this post I’ll run through a relatively simple time-series forecast that employs forcast package’s auto.arima function and regression tress to via the rpart library.
library(RCurl)
library(forecast)
library(lubridate)
library(tidyverse)
library(ggforce)
library(kableExtra)
library(rpart)
library(rpart.plot)
library(data.table)
Here’s a preview of the data I’m working with. It’s the same EMS data (with different aggregations) from my EMS Flexdashboard post.
https://jbrnbrg.
2019-02-21