# Exponential 1950s the method got extended to a

Exponential smoothing:”Exponential smoothing methods have beenaround since the 1950s, and are still the most popular forecasting methods usedin business and industry” (Rob J. Hyndman, 2008), which means that it’sone of the most successful forecasting methods.What is exponential smoothing?Exponential smoothing (SE) is a model thatsmooths the time series data using exponential purposes that gives weights reducedover time(exponentially).

It’s a popular method that creates a smoothed timeseries. Exponential smoothing can be learned easily without a difficulty. It wouldbe better to be used if a new product has few sales data but then it willprovide a steady trend prediction of the future sales.History of exponential smoothing:There are a range of strategies that fallunder exponential smoothing, each one of these methods has the property offorecasting a combination of weighted historical observations, with the latestobservations specified it will have a quite greater weight than observations atthe beginning.

In addition, exponential smoothing gets to reflect that theweights will get reduced exponentially when the observations become older.In 1944 Robert G. Brown who at that timewas working for the US Navy as an operation research analyst, where he trackedthe speed and angle submarines firing using this method in a mechanical computing.

After that in the 1950s the method got extended to a discrete time series whichwas a continuous time series at the beginning, it contained phrases to deal seasonalityand trend. At that time in 1956 presented one of his first applicationsof forecasting the demand for spare parts the inventory system of the US Navyin a meeting of the operations research society of America, then the methodswere further developed in 1963.Subsequently, Charlesholt did work after that on a different exponential smoothing model than theone Brown’s did with deference for the seasonality and trend way. His work was onadditive and multiplicative seasonal exponential smoothing in 1957.  One of holt’s students Peter Winter wrote apaper that provided empirical tests for his teacher method, the outcome of thepaper was called then Holt-Winters’ methods (or Winters).

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by 1960, Holt’s methodthen become well recognized. In 1960 Holt did collaborate with John Muth whichhe then introduced the first two long series of statistical models. Exponentialsmoothing success in forecasting lead to several researchers to find out modelsthat can produce equivalent forecasts as these methods.