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)

The date and time formats

One of the main challenges of working with date and time objects is the variety of formats that can be used for representing date and time. For example, most of the common calendar systems use an alphabetical form to represent the three date components:

  • Y: Refers to the year, which can display either using the yy (two-digits year, for example, 18) or yyyy (four-digit year, for example, 2018) formats.
  • M: Refers to the month. Here there are four methods to display the month:
    • m: One-digit month (the first 9 months represented by a single digit, for example, 1 for January, 2 for February, and so on)
    • mm: Two-digit month (the first 9 months represented by two digits, for example, 01 for January, 02 for February, and so on)
    • mmm: Three-letter abbreviation for a month (for example, Jan for January, Feb for February, and so on)
    • mmmm: Full month name (for example...