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R for Data Science

You're reading from   R for Data Science Learn and explore the fundamentals of data science with R

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781784390860
Length 364 pages
Edition 1st Edition
Languages
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Author (1):
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Dan Toomey Dan Toomey
Author Profile Icon Dan Toomey
Dan Toomey
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Toc

Table of Contents (14) Chapters Close

Questions

Factual

  • How would you compare the results of the different models and forecasts to select the appropriate constraints?
  • In the initial plot of the river data, is there something that could be used to foresee the seasonality and/or trend immediately without breaking into components?

When, how, and why?

  • While the automated selection provided ARIMA values, how would you select the different parameters?
  • How would you decide on the different modeling techniques used for your dataset?

Challenges

  • Several of the forecasts involved negative values for the river flow. How can that be avoided?
  • Either use a time series that you have available or find one that has the components addressed in the chapter and apply the analysis available in R.
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