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Hands-On Time Series Analysis with R : Perform Time Series Analysis and...
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Specificaties
- Objectstaat
- ISBN
- 9781788629157
- Publication Year
- 2019
- Type
- Textbook
- Format
- Trade Paperback
- Language
- English
- Subject Area
- Computers
- Publication Name
- Hands-On Time Series Analysis with R : Perform Time Series Analysis and Forecasting Using R
- Publisher
- Packt Publishing, The Limited
- Item Length
- 3.6 in
- Subject
- Data Modeling & Design, Mathematical & Statistical Software, Data Visualization, Data Processing
- Item Width
- 3 in
- Number of Pages
- 448 Pages
Over dit product
Product Identifiers
Publisher
Packt Publishing, The Limited
ISBN-10
1788629159
ISBN-13
9781788629157
eBay Product ID (ePID)
18038663494
Product Key Features
Number of Pages
448 Pages
Publication Name
Hands-On Time Series Analysis with R : Perform Time Series Analysis and Forecasting Using R
Language
English
Publication Year
2019
Subject
Data Modeling & Design, Mathematical & Statistical Software, Data Visualization, Data Processing
Type
Textbook
Subject Area
Computers
Format
Trade Paperback
Dimensions
Item Length
3.6 in
Item Width
3 in
Additional Product Features
Intended Audience
Trade
Table Of Content
Table of Contents Introduction to Time Series Analysis and R Working with Date and Time Objects The Time Series Object Working with zoo and xts Objects Decomposition of Time Series Data Seasonality Analysis Correlation Analysis Forecasting Strategies Forecasting with Linear Regression Forecasting with Exponential Smoothing Models Forecasting with ARIMA Models Forecasting with Machine Learning Models
Synopsis
This book introduces you to time series analysis and forecasting with R; this is one of the key fields in statistical programming and includes techniques for analyzing data to extract meaningful insights. You will explore methods, such as prediction with time series analysis, and identify the relationship between each data point in the series., 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.
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