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  2. Unevenly spaced time series - Wikipedia

    en.wikipedia.org/wiki/Unevenly_spaced_time_series

    Traces is a Python library for analysis of unevenly spaced time series in their unaltered form.; CRAN Task View: Time Series Analysis is a list describing many R (programming language) packages dealing with both unevenly (or irregularly) and evenly spaced time series and many related aspects, including uncertainty.

  3. Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Excel

    It also introduced intelligent cell re-computation, where only cells dependent on the cell being modified are updated (previous spreadsheet programs recomputed everything all the time or waited for a specific user command). Excel introduced auto-fill, the ability to drag and expand the selection box to automatically copy a cell or row contents ...

  4. Module:Table empty cell - Wikipedia

    en.wikipedia.org/wiki/Module:Table_empty_cell

    Module:Table empty cell is used to create an empty table cell with alt and title texts. Parameter list. Parameter Explanation Status alt_text; 1;

  5. Partial autocorrelation function - Wikipedia

    en.wikipedia.org/wiki/Partial_autocorrelation...

    Partial autocorrelation function of Lake Huron's depth with confidence interval (in blue, plotted around 0). In time series analysis, the partial autocorrelation function (PACF) gives the partial correlation of a stationary time series with its own lagged values, regressed the values of the time series at all shorter lags.

  6. Lag operator - Wikipedia

    en.wikipedia.org/wiki/Lag_operator

    With these time-dependent conditional expectations, there is the need to distinguish between the backshift operator (B) that only adjusts the date of the forecasted variable and the Lag operator (L) that adjusts equally the date of the forecasted variable and the information set:

  7. Moving-average model - Wikipedia

    en.wikipedia.org/wiki/Moving-average_model

    In time series analysis, the moving-average model (MA model), also known as moving-average process, is a common approach for modeling univariate time series. [1] [2] The moving-average model specifies that the output variable is cross-correlated with a non-identical to itself random-variable.

  8. Error correction model - Wikipedia

    en.wikipedia.org/wiki/Error_correction_model

    In order to still use the Box–Jenkins approach, one could difference the series and then estimate models such as ARIMA, given that many commonly used time series (e.g. in economics) appear to be stationary in first differences. Forecasts from such a model will still reflect cycles and seasonality that are present in the data.

  9. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Time series: random data plus trend, with best-fit line and different applied filters. In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time.