Hands-On Time Series Analysis with R

Build efficient forecasting models using machine learning and neural network techniques
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Hands-On Time Series Analysis with R

Rami Krispin

Build efficient forecasting models using machine learning and neural network techniques
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Book Details

ISBN 139781788629157
Paperback344 pages

Book Description

Time series analysis is one of the key fields in statistical programming and it comprises of various techniques to analyze data to extract meaningful insights and other valuable characteristics from data. This book will be introducing readers to some powerful methods such as prediction and forecasting with Time Series Analysis using R. The book will equip you with tools and techniques which will let you confidently think through the problem.

This book travels through the basics to lay the foundation required to build time series models. It allows readers to see patterns in time series data, perform modeling of data, and finally make forecasts based on those models. This book will demonstrate different ways to handle date and time data in R and will uncover the set of tools such as auto-correlation function, correlation plots, etc. to explore the relationship between each data point in the series. Readers will also get hands-on experience on tools and methods for data visualization of time series data and exposure to multivariate time series analysis in R using xts and zoo packages which provides a set of powerful tools to complete tasks with the practical approach mentioned. Here, you will get acquainted with different techniques of reading, exploring and visualizing time series data. In the later stage of the book, it will delve into different types of models such as ARMA, ARIMA models to make future predictions and forecasting to derive hidden insights to make informed decision making.

By the end of this book, you will know everything about Time-series analysis and the advanced approaches such as hybrid models, machine learning, and neural nets to build predictive models in the real world.

Table of Contents

What You Will Learn

  • The practical & easy to follow codes to evaluate the high-performance forecasting solution.
  • Develop a basic understanding of visualizing time series data in order to derive better insights.
  • Explore auto-correlation and gain knowledge of statistical techniques to deal with non-stationary time series.
  • Learn to build a Bayesian Structural Time Series model with external variables.
  • Discover how to use time series analysis tools from the stats, forecast and astsa packages.
  • Understand how to work with different time series formats in R (“ts”, “mts”, “xts” and “zoo” objects)
  • Get introduced to traditional time series models like; ARIMA, Holt-Winters, ETS, etc.

Authors

Table of Contents

Book Details

ISBN 139781788629157
Paperback344 pages
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