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  2. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    The Long Short-Term Memory (LSTM) cell can process data sequentially and keep its hidden state through time. Long short-term memory ( LSTM ) [ 1 ] is a type of recurrent neural network (RNN) aimed at mitigating the vanishing gradient problem [ 2 ] commonly encountered by traditional RNNs.

  3. Makridakis Competitions - Wikipedia

    en.wikipedia.org/wiki/Makridakis_Competitions

    The time series included yearly, quarterly, monthly, daily, and other time series. In order to ensure that enough data was available to develop an accurate forecasting model, minimum thresholds were set for the number of observations: 14 for yearly series, 16 for quarterly series, 48 for monthly series, and 60 for other series.

  4. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    The original model uses an iterative three-stage modeling approach: Model identification and model selection: making sure that the variables are stationary, identifying seasonality in the dependent series (seasonally differencing it if necessary), and using plots of the autocorrelation (ACF) and partial autocorrelation (PACF) functions of the dependent time series to decide which (if any ...

  5. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    Unlike feedforward neural networks, which process data in a single pass, RNNs process data across multiple time steps, making them well-adapted for modelling and processing text, speech, and time series. [1] The building block of RNNs is the recurrent unit. This unit maintains a hidden state, essentially a form of memory, which is updated at ...

  6. Autoregressive integrated moving average - Wikipedia

    en.wikipedia.org/wiki/Autoregressive_integrated...

    Specifically, for a wide-sense stationary time series, the mean and the variance/autocovariance are constant over time. Differencing in statistics is a transformation applied to a non-stationary time-series in order to make it stationary in the mean sense (that is, to remove the non-constant trend), but it does not affect the non-stationarity ...

  7. Rob J. Hyndman - Wikipedia

    en.wikipedia.org/wiki/Rob_J._Hyndman

    Robin John Hyndman (born 2 May 1967 [citation needed]) is an Australian statistician known for his work on forecasting and time series. He is a Professor of Statistics at Monash University [ 1 ] and was Editor-in-Chief of the International Journal of Forecasting from 2005–2018. [ 2 ]

  8. Time running out for top free agents, Orioles’ sign Morton ...

    www.aol.com/sports/time-running-top-free-agents...

    Jake Mintz and Jordan Shusterman discuss where the top remaining free agents might wind up with time running out, the Orioles signing Charlie Morton, Korean free agent Hyeseong Kim joining the ...

  9. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values.