Book Image

Hands-On Time Series Analysis with R

By : Rami Krispin
Book Image

Hands-On Time Series Analysis with R

By: Rami Krispin

Overview of this book

Time-series analysis is the art of extracting meaningful insights from, and revealing patterns in, time-series data using statistical and data visualization approaches. These insights and patterns can then be utilized to explore past events and forecast future values in the series. This book explores the basics of time-series analysis with R and lays the foundation you need to build forecasting models. You will learn how to preprocess raw time-series data and clean and manipulate data with packages such as stats, lubridate, xts, and zoo. You will analyze data using both descriptive statistics and rich data visualization tools in R including the TSstudio, plotly, and ggplot2 packages. The book then delves into traditional forecasting models such as time-series linear regression, exponential smoothing (Holt, Holt-Winter, and more) and Auto-Regressive Integrated Moving Average (ARIMA) models with the stats and forecast packages. You'll also work on advanced time-series regression models with machine learning algorithms such as random forest and Gradient Boosting Machine using the h2o package. By the end of this book, you will have developed the skills necessary for exploring your data, identifying patterns, and building a forecasting model using various traditional and machine learning methods.
Table of Contents (14 chapters)

Forecasting a series with multiseasonality components – a case study

One of the main advantages of the regression model, as opposed to the traditional time series models such as ARIMA or Holt-Winters, is that it provides a wide range of customization options and allows us to model and forecast complex time series data such as series with multiseasonality.

In the following examples, we will use the UKgrid series to demonstrate the forecasting approach of a multiseasonality series with a linear regression model.

The UKgrid series

The UKgrid series represents the national grid demand for electricity in the UK, and it is available in the UKgrid package. This series represents a high-frequency time series data with half...