Forecasting with exponential smoothing Anne B. Koehler, J. Keith Ord, Ralph D. Snyder, Rob Hyndman
Publisher: Springer

Exponential smoothing is one of the most common techniques that is applied to time series data to make forecasts. Statistical forecasting enables you to use detailed history and applies weighting factors to exponentially smooth the data. Forecasting is widely used in management and Excel allows us to solve simple forecasting tasks. Finding the components is difficult. I'm using exponential smoothing (Brown's method) for forecasting. The forecast can be calculated for one or more steps (time intervals). However, we can also use smoothing to fill in missing values and/or conduct a forecast. The forecast value is computed from. Further we demonstrate the Holt's technique for double exponential smoothing in a linear upwards trend and how we can use it for forecasting. So we pass our data set and get the best forecast model that can use to train our data set. It is used alot in retail and service industries. Is there any way to calculate confidence intervals for such prognosis (ex-ante)? A direct approach averages past Yt values by exponential smoothing. Exponential smoothing is the most used of all forecasting techniques and appears in all computer based forecasting applications. Winter Model – Exponential Smoothing Adjusted for Trend and Seasonal Times series decomposition.