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Effective Short-Term Forecasting for Daily Time Series with Complex Seasonal Patterns
11 references·0 citing·42 second hop
Effective Short-Term Forecasting for Daily Time Series with Complex Seasonal Patterns (2018)Effective Short-Term Forecasting for Dail…Forecasting the price of gold (2015)Forecasting the price of goldForecasting household natural gas consumption with ARIMA model: A case study of removing cycle (2013)Forecasting household natural…Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)Forecasting Time Series With …Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing (2011)Forecasting intraday time ser…Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles (2010)Exponentially weighted method…Forecasting time series with multiple seasonal patterns (2007)Forecasting time series with …Forecasting daily supermarket sales using exponentially weighted quantile regression (2006)Forecasting daily supermarket…ARIMA forecasting of primary energy demand by fuel in Turkey (2006)ARIMA forecasting of primary …Error measures for generalizing about forecasting methods: Empirical comparisons (1992)Error measures for generalizi…Forecasting: Methods and Applications. (1979)Forecasting: Methods and Appl…Forecasting principles and practiceForecasting principles and pr…Exponential smoothing: The state of the art (1985)Telephone Call Centers: Tutorial, Review, and Research Prospects (2003)CAViaR (2004)Temporal hierarchies with autocorrelation for load forecasting (2019)Deep-learning model using hybrid adaptive trend estimated series for modelling and forecasting sales (2022)Macroeconomics and Reality (1980)Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models (1991)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Predicting Future Gold Rates using Machine Learning Approach (2017)Ensemble forecasting for product futures prices using variational mode decomposition and artificial neural networks (2021)Predicting Gold and Silver Price Direction Using Tree-Based Classifiers (2021)Exponential smoothing: The state of the art—Part II (2006)Forecasting IT security vulnerabilities – An empirical analysis (2019)Optimal selection of heterogeneous ensemble strategies of time series forecasting with multi-objective programming (2020)Exponential Smoothing on Modeling and Forecasting Multiple Seasonal Time Series: An Overview (2021)Forecasting, Structural Time Series Models and the Kalman Filter (1990)Evaluating Interval Forecasts (1998)Prediction intervals for exponential smoothing using two new classes of state space models (2005)The value of competitive information in forecasting FMCG retail product sales and the variable selection problem (2014)Time Series Analysis: Forecasting and Control (1977)Energy consumption and GDP: causality relationship in G-7 countries and emerging markets (2002)Time series forecasting using a hybrid ARIMA and neural network model (2003)Forecasting time series using a methodology based on autoregressive integrated moving average and genetic programming (2010)Modeling and forecasting of Turkey’s energy consumption using socio-economic and demographic variables (2010)Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition (2019)The accuracy of extrapolation (time series) methods: Results of a forecasting competition (1982)A state space framework for automatic forecasting using exponential smoothing methods (2002)Making and Evaluating Point Forecasts (2011)A new metric of absolute percentage error for intermittent demand forecasts (2016)Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. (1978)Another look at measures of forecast accuracy (2006)Automatic Time Series Forecasting: The forecast Package for R (2008)Forecasting Destination Weekly Hotel Occupancy with Big Data (2016)Structural combination of seasonal exponential smoothing forecasts applied to load forecasting (2018)Forecasting: theory and practice (2022)A Comparison of ARIMA and LSTM in Forecasting Time Series (2018)The Performance of LSTM and BiLSTM in Forecasting Time Series (2019)Recurrent Neural Networks for Time Series Forecasting: Current status and future directions (2020)Achieving competitive advantage through implementing a replicable management standard: Installing and using ISO 9000 (2005)Lee-Carter mortality forecasting: a multi-country comparison of variants and extensions (2006)Robust forecasting with exponential and Holt–Winters smoothing (2009)
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References

  • n.d.Forecasting principles and practice4,364 cited
  • 1992Error measures for generalizing about forecasting methods: Empirical comparisons1,400 cited
  • 1979Forecasting: Methods and Applications.1,237 cited
  • 2011Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing1,055 cited
  • 2006ARIMA forecasting of primary energy demand by fuel in Turkey622 cited
  • 2007Forecasting time series with multiple seasonal patterns189 cited
  • 2006Forecasting daily supermarket sales using exponentially weighted quantile regression123 cited
  • 2010Exponentially weighted methods for forecasting intraday time series with multiple seasonal cycles92 cited
  • 2011Forecasting intraday time series with multiple seasonal cycles using parsimonious seasonal exponential smoothing85 cited
  • 2015Forecasting the price of gold79 cited
  • 2013Forecasting household natural gas consumption with ARIMA model: A case study of removing cycle42 cited

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