Please Enter ISBN, Title or Author’s Name
Compare Textbook Prices with Amazon
Compare Textbook Prices with Chegg
Compare Textbook Prices with AbeBooks
Compare Textbook Prices with Vitalsource
Compare Textbook Prices with Valorebooks
and more...

Hands-On Time Series Analysis with R

Compare Textbook Prices for Hands-On Time Series Analysis with R  ISBN 9781788629157 by Krispin, Rami
Author: Krispin, Rami
ISBN:1788629159
ISBN-13: 9781788629157
List Price: $33.29 (up to 21% savings)
Prices shown are the lowest from
the top textbook retailers.

View all Prices by Retailer

Details about Hands-On Time Series Analysis with R:

Build efficient forecasting models using traditional time series models and machine learning algorithms. Key Features Perform time series analysis and forecasting using R packages such as Forecast and h2o Develop models and find patterns to create visualizations using the TSstudio and plotly packages Master statistics and implement time-series methods using examples mentioned Book Description 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 foundations 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 and extract meaningful information from it using both descriptive statistics and rich data visualization tools in R such as the TSstudio, plotly, and ggplot2 packages. The later section of the book 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 cover 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 the skills needed to explore your data, identify patterns, and build a forecasting model using various traditional and machine learning methods. What you will learn Visualize time series data and derive better insights Explore auto-correlation and master statistical techniques Use time series analysis tools from the stats, TSstudio, and forecast packages Explore and identify seasonal and correlation patterns Work with different time series formats in R Explore time series models such as ARIMA, Holt-Winters, and more Evaluate high-performance forecasting solutions Who this book is for Hands-On Time Series Analysis with R is ideal for data analysts, data scientists, and all R developers who are looking to perform time series analysis to predict outcomes effectively. A basic knowledge of statistics is required; some knowledge in R is expected, but not mandatory.

Need Professional tutors? Start your search below:
Need Professional course notes? Start your search below: