Сalculates or predicts a future value based on existing (historical) values by using the AAA version of the Exponential Smoothing (ETS) algorithm.
| Name | Type | Description |
| arg1 | number | A date for which a new value will be predicted. Must be after the last date in the timeline. |
| arg2 | ApiRange | Array.<number> | A range or an array of numeric data that determines the historical values for which a new point will be predicted. |
| arg3 | ApiRange | A range of date/time values that correspond to the historical values. The timeline range must be of the same size as the second argument. Date/time values must have a constant step between them and can't be zero. |
| arg4 | number | An optional numeric value that specifies the length of the seasonal pattern. The default value of 1 indicates seasonality is detected automatically. The 0 value means no seasonality. |
| arg5 | number | An optional numeric value to handle missing values. The default value of 1 replaces missing values by interpolation, and 0 replaces them with zeros. |
| arg6 | Aggregation | An optional numeric value to aggregate multiple values with the same time stamp. |
builder.CreateFile("xlsx");
var oWorksheet = Api.GetActiveSheet();
var oFunction = Api.GetWorksheetFunction();
var dates = ["10/1/2017", "11/1/2017", "12/1/2017", "1/1/2018", "2/1/2018", "3/1/2018"];
var numbers = [12558, 14356, 16345, 18678, 14227];
for (var i = 0; i < dates.length; i++) {
oWorksheet.GetRange("A" + (i + 1)).SetValue(dates[i]);
}
for (var j = 0; j < numbers.length; j++) {
oWorksheet.GetRange("B" + (j + 1)).SetValue(numbers[j]);
}
oWorksheet.GetRange("A1").SetColumnWidth(15);
var oRange1 = oWorksheet.GetRange("B1:B5");
var oRange2 = oWorksheet.GetRange("A1:A5");
oWorksheet.GetRange("B6").SetValue(oFunction.FORECAST_ETS("3/1/2018", oRange1, oRange2, 0, 1, 1));
builder.SaveFile("xlsx", "FORECAST_ETS.xlsx");
builder.CloseFile();