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Practical Time Series Analysis

You're reading from   Practical Time Series Analysis Master Time Series Data Processing, Visualization, and Modeling using Python

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781788290227
Length 244 pages
Edition 1st Edition
Languages
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Authors (2):
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Avishek Pal Avishek Pal
Author Profile Icon Avishek Pal
Avishek Pal
PKS Prakash PKS Prakash
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PKS Prakash
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Toc

Second order exponential smoothing

If first order exponential smoothing does not perform well, then there is a trend in the time series data. The trend is commonly observed in many domains such as when marketing campaigns are run by e-commerce companies, the sales rise or any good annual performance by a company will have a bullish effect on its stock prices. The linear trend can occur due to linear trend between time and response:

xt = constant + ωt + εt

Here, ω is the coefficient that leads to trend. The second order exponential smoothing helps capture the trend in time series data by including another term to the first order exponential smoothing as follows:

Here, Tt captures the trend component of the exponential smoothing and is represented as follows:

Here, α is the data smoothing factor and β is the trend smoothing factor with values between...

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