Introduction to Time Series Analysis and Forecasting

By Theresa L. Utlaut. 2008

1,517 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/f2e00dc73d29a9358be0a1bd0aac3f71ec916fc8

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In Signal Processing

Citations in the corpus

The Impact of Structured Event Embeddings on Scalable Stock Forecasting Models (2015, methodology): “However, in recent years successful modern models not based on auto regression have been proposed as, for instance, the work by [15].”
Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques (2019, methodology): “Statistical methods are based on a sequence of observations of one or more parameters measured at successive instants in time [21].”
Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm (2012, background): “However, having a small training error that is too small may degrade the generalization capability on the shortterm traffic flow forecasting on unseen data.”
Fine-Grained Photovoltaic Output Prediction Using a Bayesian Ensemble (2012, background): “Related Work Comprehensive surveys on time series prediction (Brockwell and Davis 2002; Montgomery, Jennings, and Kulahci 2008) exist that provide overviews of classical methods from ARMA to modeling heteroskedasticity (we implement some of these in this paper for comparison purposes).”
Deep Learning Based Forecasting of Critical Infrastructure Data (2017, methodology): “Although the general TSF problem has a rich history within the data mining and statistical machine learning community [3, 34], and a variety of stand-alone as well as ensemble methods have been proposed to handle the problem [6, 11], it is still one of the pivotal topics in the context of time…”
Spatio-Temporal Data Mining (2017, background): “Similar problems are studied in predicting closing stock prices at the New York Stock Exchange and in predicting sales in the manufacturing industry (Montgomery et al. 2015).”
SutteARIMA: Short-term forecasting method, a case: Covid-19 and stock market in Spain (2020, background): “Zt  define stationarity (or weak stationarity) as follows (Brockwell and Davis, 2016; Montgomery et al., 2015) : ”