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Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R

By : Rami Krispin
3.9 (10)
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Hands-On Time Series Analysis with R

Hands-On Time Series Analysis with R

3.9 (10)
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)
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The attributes of the ts class

The ts class is R's built-in format for a regular univariate time series object. Before we dive into the attributes of this class, let's pause and define regular time series data and its main characteristics.

At regular time series is defined as an ordered sequence of observations over time, which is captured at equally spaced time intervals (that is, every day, week, month, and so on). Whenever this condition ceases to exist, the series becomes an irregular time series. Since this book's main topic is time series analysis and the forecasting of regular time series data, the term time series, or series, refers to regular time series data unless stated otherwise.

The main characteristics of regular time series data is as follows:

  • Cycle/period: A regular and repeating unit of time that split the series into consecutive and equally long...
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Hands-On Time Series Analysis with R
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