[读者文库]Introduction to Time Series Analysis and Forecasting(using R)

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Series: Wiley Series in Probability and Statistics
Hardcover: 672 pages
Publisher: Wiley; 2 edition (May 4, 2015)
Author: Douglas Montgomery
Language: English
ISBN-10: 1118745116
ISBN-13: 978-1118745113

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关键词：introduction Forecasting Time Series troduction Analysis

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1. Example 3.3 For this example we will use the “lm” function.
   
2. satisfaction2.fit<-lm(Satisfaction ~ Age+Severity+Age:Severity+I(Ageˆ2)+
   
3. I(Severityˆ2), data=patsat)
   
4. summary(satisfaction2.fit)

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Example 3.13
We repeat Example 3.12 with the model expanded to include Population as well.

1. soft2.fit<-lm(Sales ~ Expenditures+Population, data=softsales.data)dwt(soft2.fit, alternative=”positive”)

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As concluded in the example, adding the input variable Population seems to resolve the autocorrelation issue resulting in large p-value for the test for autocorrelation.