Provides a thorough coverage and comparison of a wide array of time
series models and methods: Exponential Smoothing, Holt Winters,
ARMA and ARIMA, deep learning models including RNNs, LSTMs, GRUs,
and ensemble models composed of combinations of these models.
Introduces the factor table representation of ARMA and ARIMA
models. This representation is not available in any other book at
this level and is extremely useful in both practice and pedagogy.
Uses real world examples that can be readily found via web links
from sources such as the US Bureau of Statistics, Department of
Transportation and the World Bank. There is an accompanying R
package that is easy to use and requires little or no previous R
experience. The package implements the wide variety of models and
methods presented in the book and has tremendous pedagogical use.
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