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  2. Fan chart (time series) - Wikipedia

    en.wikipedia.org/wiki/Fan_chart_(time_series)

    There are several ways to represent the forecast density depending on the shape of the forecasting distribution. If the forecast density is symmetric ( normal or Student's t , for instance), the fan centers at the mean (which coincides with the mode and median ) forecast, and the ranges expand like confidence intervals by adding and subtracting ...

  3. Javelin Software - Wikipedia

    en.wikipedia.org/wiki/Javelin_Software

    Although Excel was a beautiful extension of the existing spreadsheet concept, Javelin had imaginative features, says Michael McCarthy, InfoWorld reviews editor from 1984 to 1990 and current publisher of IDG's San Francisco-based Web Publishing Inc., producers of JavaWorld and SunWorld. "I persuaded InfoWorld to give Javelin Product of the Year ...

  4. Data assimilation - Wikipedia

    en.wikipedia.org/wiki/Data_assimilation

    The difference between the forecast and the observations at that time is called the departure or the innovation (as it provides new information to the data assimilation process). A weighting factor is applied to the innovation to determine how much of a correction should be made to the forecast based on the new information from the observations.

  5. FAME (database) - Wikipedia

    en.wikipedia.org/wiki/FAME_(database)

    FAME Desktop Add-in for Excel: FAME Desktop is an Excel add-in that supports the =FMD(expression, sd, ed,0, freq, orientation) and =FMS(expression, freq + date) formulas, just as the 4GL command prompt does. These formulas can be placed in Excel spreadsheets and are linked to FAME objects and analytics stored on a FAME server. Sample Excel ...

  6. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Time series forecasting is the use of a model to predict future values based on previously observed values. Generally, time series data is modelled as a stochastic process .

  7. Multivariate interpolation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_interpolation

    ) and the interpolation problem consists of yielding values at arbitrary points (,,, … ) {\displaystyle (x,y,z,\dots )} . Multivariate interpolation is particularly important in geostatistics , where it is used to create a digital elevation model from a set of points on the Earth's surface (for example, spot heights in a topographic survey or ...

  8. Nearest-neighbor interpolation - Wikipedia

    en.wikipedia.org/wiki/Nearest-neighbor_interpolation

    Nearest-neighbor interpolation (also known as proximal interpolation or, in some contexts, point sampling) is a simple method of multivariate interpolation in one or more dimensions. Interpolation is the problem of approximating the value of a function for a non-given point in some space when given the value of that function in points around ...

  9. Regression-kriging - Wikipedia

    en.wikipedia.org/wiki/Regression-kriging

    In applied statistics and geostatistics, regression-kriging (RK) is a spatial prediction technique that combines a regression of the dependent variable on auxiliary variables (such as parameters derived from digital elevation modelling, remote sensing/imagery, and thematic maps) with interpolation of the regression residuals.