SMOOTHIE evaluates time-series data to construct a forecasting model using single and double exponential smoothing, moving average, trend, arithmetic mean, and complete decomposition methods.
Input requirements.
- Title. The user should enter a title for the data in the top form field.
- Observations. A set of time-series data in free format: a series of observed values for a single variable, taken at uniform time intervals, given in chronological order, and separated by blanks or on separate lines.
- Number of periods for error calculations. the number of observations to be used in calculating cumulative error values, such as mean squared error (MSE). Since the models result in varying numbers of historical error terms, one may wish to use a subset in computing cumulatives, if the values are to be compared across models.
- Choice of forecasting model. Using the radio buttons, one of the following forecasting models is selected and any related parameter values entered:
- Moving average, requires: number of periods to average over
- Exponential smoothing (single), requires: alpha, a smoothing constant between 0 and 1
- Smoothing with trend (double), requires: alpha (0-1, emphasis on recent values) and beta (0-1, weight on trend component)
- Trend, fits regression line to data using time as the independent variable
- Arithmetic mean, forecast is the average of all historical values
- Decomposition of data into trend, seasonal, cyclical, and irregular/random components, requires: specification of monthly or quarterly nature of data
Sample data
The following quarterly data may be copied and pasted into the Input time-series data here field.
13.1 12 15.8 11.4 14 15.3 17.6 13 15.2 16.4 19.2 14.7 15.6 15.5 17.2 16.7 16.8 16.5 17.4 14.4 17.0 19.4 19.2 16.7
Add a title, select a forecasting model, and press the Run Smoothie button.
Sample dataset 2
Quarterly new car sales in U.S., 1958-1974
1069 1142 927 1151 1323 1613 1289 1263 1515 1739 1330 1559 1212 1550 1180 1624 1559 1887 1360 1946 1721 2056 1498 2059 1844 2171 1753 1895 2196 2381 1822 2366 2207 2209 1744 2218 1744 2235 1692 1897 2021 2321 1934 2349 2030 2347 1927 2161 1782 2189 1654 1490 1977 2281 1988 2676 2078 2537 2165 2541 2473 2742 2247 2208 1771 2166 1949 1562
In-class example:
120 124 122 123 125 128 129 127 129 128 130
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