Spread.NET 16 Formula Reference
Formula Functions / Functions D to G / FORECAST.ETS.STAT
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    FORECAST.ETS.STAT
    In This Topic

    This function return a statistical value as a result of time series forecasting. Statistic type indicates which statistic is requested by this function.

    Syntax

    =FORECAST.ETS.STAT(values,timeline,statistic_type,[seasonality],[data_completion],[aggregation])

    Arguments

    The function has the following arguments:

    Argument

    Description

    values [Required] is a range of the historical values for which you want to predict a new point.
    timeline

    [Required] is a range of date/time values that correspond to the historical values. The timeline range must be of the same size as the values range. Date/time values must have a constant step between them.

    statistic_type

    [Required] A numeric value between 1 and 8, indicating which statistic will be returned for the calculated forecast.

    The table below shows the eight possible statistical values and their corresponding results.

    Value Statistic type Description
    1 Alpha It is the base parameter of ETS algorithm. Higher values indicate more weight to recent data.
    2 Beta It is the trend parameter of ETS algorithm. Higher values indicate more weight to recent trends.
    3 Gamma It is the seasonality parameter of ETS algorithm. Higher values indicate more weight to recent seasonal periods.
    4 MASE It stands for Mean Absolute Scaled Error metric, a measure of forecast accuracy.
    5 SMAPE It stands for Symmetric Mean Absolute Percentage Error metric, an accuracy measure based on percentage errors.
    6 MAE It stands for the Mean Absolute percentage Error metric, a measure of accuracy based on percentage errors.
    7 RMSE It stands for Root Mean Squared Error metric, a measure of differences between predicted and observed values.
    8 Step Size It is detected in the historical data timeline.
    seasonality

    [Optional] is a numeric value that specifies which method should be used to detect the seasonality. The possible values are listed in the table below.

    • 1 or omitted:  Seasonality is detected automatically. Positive, whole numbers are used for the length of the seasonal pattern.
    • 0:  No seasonality, the prediction will be linear.
    • an integer greater than or equal to 2: The specified number is used for the length of the seasonal pattern.
    data_completion

    [Optional] is a numeric value that specifies how to process the missing data points in the timeline data range. The possible values are listed below.

    • 1 or omitted:  Missing points are calculated as the average of the neighboring points.
    • 0:  Missing points are treated as zero values.
    aggregation

    [Optional] is a numeric value that specifies which function should be used to aggregate identical time values in the timeline data range. The possible values are listed below.

    Numeric Value Function
    1 or omitted AVERAGE

    2

    COUNT

    3

    COUNTA

    4

    MAX

    5

    MEDIAN

    6

    MIN
    7 SUM

    Data Types

    Returns a specified statistical value relating to a time series.

    Examples

    Version Available

    This function is available in product version 16.0 or later.