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)

Structural tools for seasonal analysis

Data visualization methods have a pivotal role in time series analysis, and in particular with seasonal analysis. As we saw in the preceding examples, the use of data visualization tools allows us to communicate statistical results in an intuitive and insightful way. In the coming sections, we will introduce built-in tools for seasonal analysis with the forecast and TSstudio packages.

Seasonal analysis with the forecast package

The forecast package provides several functions for seasonal analysis based on the ggplot2 package graphics engine (and the base plot function) and it supports the ts objects. The ggseasonplot function creates a seasonal plot of the series by splitting and plotting...