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  2. Peter Riegel - Wikipedia

    en.wikipedia.org/wiki/Peter_Riegel

    Peter Riegel (January 30, 1935 – May 28, 2018) was an American research engineer who developed a mathematical formula for predicting race times for runners and other athletes given a certain performance at another distance. The formula has been widely adopted on account of its simplicity and predictive accuracy.

  3. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    All have the same trend, but more filtering leads to higher r 2 of fitted trend line. The least-squares fitting process produces a value, r-squared (r 2), which is 1 minus the ratio of the variance of the residuals to the variance of the dependent variable. It says what fraction of the variance of the data is explained by the fitted trend line.

  4. Tracking signal - Wikipedia

    en.wikipedia.org/wiki/Tracking_signal

    One form of tracking signal is the ratio of the cumulative sum of forecast errors (the deviations between the estimated forecasts and the actual values) to the mean absolute deviation. [1] The formula for this tracking signal is:

  5. Bass diffusion model - Wikipedia

    en.wikipedia.org/wiki/Bass_diffusion_model

    The Bass model has been widely used in forecasting, especially new product sales forecasting and technology forecasting. Mathematically, the basic Bass diffusion is a Riccati equation with constant coefficients equivalent to Verhulst—Pearl logistic growth. In 1969, Frank Bass published his paper on a new product growth model for consumer ...

  6. Forecast skill - Wikipedia

    en.wikipedia.org/wiki/Forecast_skill

    In this case, a perfect forecast results in a forecast skill metric of zero, and skill score value of 1.0. A forecast with equal skill to the reference forecast would have a skill score of 0.0, and a forecast which is less skillful than the reference forecast would have unbounded negative skill score values. [4] [5]

  7. 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 .

  8. Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Excel

    Microsoft Excel is a spreadsheet editor developed by Microsoft for Windows, macOS, Android, iOS and iPadOS.It features calculation or computation capabilities, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications (VBA).

  9. Probabilistic forecasting - Wikipedia

    en.wikipedia.org/wiki/Probabilistic_forecasting

    Probabilistic forecasting summarizes what is known about, or opinions about, future events. In contrast to single-valued forecasts (such as forecasting that the maximum temperature at a given site on a given day will be 23 degrees Celsius, or that the result in a given football match will be a no-score draw), probabilistic forecasts assign a probability to each of a number of different ...

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