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CANDU FIRE DATABASE (2018)CANDU FIRE DATABASEForecasting the REITs and stock indices: Group Method of Data Handling Neural Network approach (2016)Forecasting the REITs and sto…Exponential smoothing: The state of the art—Part II (2006)Exponential smoothing: The st…Forecasting seasonals and trends by exponentially weighted moving averages (2004)Forecasting seasonals and tre…Some Properties of a Simple Moving Average when Applied to Forecasting a Time Series (1999)Some Properties of a Simple M…Exponential smoothing: The state of the art (1985)Exponential smoothing: The st…Book Review: Time Series Analysis: Forecasting and Control (1977)Book Review: Time Series Anal…Forecasting Sales by Exponentially Weighted Moving Averages (1960)Forecasting Sales by Exponent…Optimal Properties of Exponentially Weighted Forecasts (1960)Forecasting Practices in US Corporations: Survey Results (1994)FORECASTING OF INTERMITTENT DEMAND (2001)Forecasting for intermittent demand: the estimation of an unbiased average (2005)Old dog, new tricks: a modelling view of simple moving averages (2017)The M3-Competition: results, conclusions and implications (2000)Forecasting Time Series With Complex Seasonal Patterns Using Exponential Smoothing (2011)Statistical and Machine Learning forecasting methods: Concerns and ways forward (2018)The M4 Competition: 100,000 time series and 61 forecasting methods (2019)Time Series Analysis: Forecasting and Control (1977)Forecasting Economic Time Series (2000)Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results (2003)Automatic Time Series Forecasting: The forecast Package for R (2008)Forecasting at Scale (2017)Testing the null hypothesis of stationarity against the alternative of a unit root (1992)Retail Property Price Index Forecasting through Neural Networks (2022)A Gaussian process regression machine learning model for forecasting retail property prices with Bayesian optimizations and cross-validation (2023)Machine learning-based forecasts of residential property prices in Hangzhou City, Zhejiang Province, China (2024)25 years of time series forecasting (2006)A new metric of absolute percentage error for intermittent demand forecasts (2016)N-BEATS: Neural basis expansion analysis for interpretable time series forecasting (2019)Distribution of the Estimators for Autoregressive Time Series With a Unit Root (1979)Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root (1981)Generalized autoregressive conditional heteroskedasticity (1986)
this work references cited by second hop

References

  • 1977Book Review: Time Series Analysis: Forecasting and Control19,399 cited
  • 1960Forecasting Sales by Exponentially Weighted Moving Averages2,149 cited
  • 2004Forecasting seasonals and trends by exponentially weighted moving averages1,786 cited
  • 1985Exponential smoothing: The state of the art1,480 cited
  • 2006Exponential smoothing: The state of the art—Part II984 cited
  • 1999Some Properties of a Simple Moving Average when Applied to Forecasting a Time Series132 cited
  • 2016Forecasting the REITs and stock indices: Group Method of Data Handling Neural Network approach92 cited

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