By Galit Shmueli
Functional Time sequence Forecasting is a hands-on creation to quantitative forecasting of time sequence. Quantitative forecasting is a crucial component to choice making in quite a lot of parts and throughout many enterprise capabilities together with monetary forecasting, workload projections, revenues forecasts, and transportation call for. Forecasting is favourite additionally outdoor of industrial, comparable to in demography and climatology.
The ebook introduces readers to the preferred statistical versions and knowledge mining algorithms utilized in perform. It covers concerns on the subject of diverse steps of the forecasting approach, from target definition via information assortment, visualization, pre-processing, modeling, functionality assessment to implementation and communication.
The moment version bargains a large number of new content material and more suitable association. functional Time sequence Forecasting is appropriate for classes on forecasting on the upper-undergraduate and graduate degrees. It deals transparent reasons, examples, end-of-chapter difficulties and a case. tools are illustrated utilizing XLMiner, an Excel add-on. even if, any software program that has time sequence forecasting services can be utilized with the booklet.
Galit Shmueli is the SRITNE Chaired Professor of information Analytics on the Indian tuition of industrial. She is co-author of the textbook facts Mining for enterprise Intelligence and the ebook Modeling on-line Auctions, between a number of different books and lots of courses in expert journals. She has been instructing classes on forecasting, information mining and different facts analytics issues on the Indian institution of industrial, collage of Maryland’s Smith tuition of industrial, and on-line at Statistics.com.
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Extra resources for Practical Time Series Forecasting: A Hands-On Guide [2nd Edition]
No part of this work may be used or reproduced, transmitted, stored or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks or information storage and retrieval systems, or in any manner whatsoever without prior written permission. 1 Forecasting: Where? 4 Goal Definition Descriptive vs. 3 Measuring Predictive Accuracy Common Prediction Accuracy Measures Zero counts Forecast Accuracy vs.
Governments forecast tax receipts and spending. International financial organizations such as the World Bank and International Monetary Fund forecast inflation and economic activity. Passenger transport companies use time series to forecast future travel. Banks and lending institutions forecast new home purchases, and venture capital firms forecast market potential to evaluate business plans. 2 Basic Notation The amount of notation in the book is kept to the necessary minimum. Let us introduce the basic notation used in the book.
4 for details). 2 Naive Forecasts Although it is tempting to apply "sophisticated" forecasting methods, one must remember to consider naive forecasts. A naive forecast is simply the most recent value of the series. , forecast December using last December's value). For a series with M seasons, we can write the formula The underlying logic is that the most recent information is likely to be the most relevant for forecasting the future. Naive forecasts are used for two purposes: As the actual forecasts of the series.