Time Series Analysis: Forecasting and Control

By Michael D. Geurts, G. Box, Gwilym M. Jenkins. 1977

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Vasilis Dakos
2. Yoshua Bengio
3. David Kristjanson Duvenaud
4. Ruslan Salakhutdinov
5. Roger Baker Grosse
6. Zoubin Ghahramani
7. Sergey Levine
8. Josh Tenenbaum

Citations in the corpus

• Time-series forecasting with deep learning: a survey (2020, neutral): “s well as commercial decision making in retail [4] and finance [5] to name a few. While traditional methods have focused on parametric models informed by domain expertise – such as autoregressive (AR) [6], exponential smoothing [7] or structural time series models [8] – modern machine learning method”
• Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data (2012, methodology): “r1 and a1 are mathematically equivalent [21].”