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  2. Interrupted time series - Wikipedia

    en.wikipedia.org/wiki/Interrupted_time_series

    Interrupted time series design is the design of experiments based on the interrupted time series approach. The method is used in various areas of research, such as: political science : impact of changes in laws on the behavior of people; [ 2 ] (e.g., Effectiveness of sex offender registration policies in the United States )

  3. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    Panel data is the general class, a multidimensional data set, whereas a time series data set is a one-dimensional panel (as is a cross-sectional dataset). A data set may exhibit characteristics of both panel data and time series data. One way to tell is to ask what makes one data record unique from the other records.

  4. Unevenly spaced time series - Wikipedia

    en.wikipedia.org/wiki/Unevenly_spaced_time_series

    Ideally, unevenly spaced time series are analyzed in their unaltered form. However, most of the basic theory for time series analysis was developed at a time when limitations in computing resources favored an analysis of equally spaced data, since in this case efficient linear algebra routines can be used and many problems have an explicit ...

  5. Box–Jenkins method - Wikipedia

    en.wikipedia.org/wiki/Box–Jenkins_method

    The original model uses an iterative three-stage modeling approach: Model identification and model selection: making sure that the variables are stationary, identifying seasonality in the dependent series (seasonally differencing it if necessary), and using plots of the autocorrelation (ACF) and partial autocorrelation (PACF) functions of the dependent time series to decide which (if any ...

  6. Time series database - Wikipedia

    en.wikipedia.org/wiki/Time_series_database

    Time series datasets can also have fewer relationships between data entries in different tables and don't require indefinite storage of entries. [6] The unique properties of time series datasets mean that time series databases can provide significant improvements in storage space and performance over general purpose databases. [ 6 ]

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  8. 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.

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