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  2. Time series database - Wikipedia

    en.wikipedia.org/wiki/Time_series_database

    A time series database is a software system that is optimized for storing and serving time series through associated pairs of time(s) and value(s). [1] In some fields, time series may be called profiles, curves, traces or trends. [ 2 ]

  3. Dart (programming language) - Wikipedia

    en.wikipedia.org/wiki/Dart_(programming_language)

    The third Dart-to-JavaScript compiler is dart2js. Introduced in Dart 2.0, [36] the Dart-based dart2js evolved from earlier compilers. It intended to implement the full Dart language specification and semantics. Developers use this compiler for production builds. It compiles to minified JavaScript. The fourth Dart-to-JavaScript compiler is ...

  4. Exponential smoothing - Wikipedia

    en.wikipedia.org/wiki/Exponential_smoothing

    Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned ...

  5. RRDtool - Wikipedia

    en.wikipedia.org/wiki/RRDtool

    RRDtool has a graph function, which presents data from an RRD in a customizable graphical format. RRDtool (round-robin database tool) aims to handle time series data such as network bandwidth, temperatures or CPU load. The data is stored in a circular buffer based database, thus the system storage footprint remains constant over time.

  6. Plotly - Wikipedia

    en.wikipedia.org/wiki/Plotly

    Plotly was founded by Alex Johnson, Jack Parmer, Chris Parmer, and Matthew Sundquist. [2]The founders' backgrounds are in science, energy, and data analysis and visualization. [2]

  7. Time series - Wikipedia

    en.wikipedia.org/wiki/Time_series

    In time-series segmentation, the goal is to identify the segment boundary points in the time-series, and to characterize the dynamical properties associated with each segment. One can approach this problem using change-point detection , or by modeling the time-series as a more sophisticated system, such as a Markov jump linear system.

  8. Autocorrelation - Wikipedia

    en.wikipedia.org/wiki/Autocorrelation

    It is common practice in some disciplines (e.g. statistics and time series analysis) to normalize the autocovariance function to get a time-dependent Pearson correlation coefficient. However, in other disciplines (e.g. engineering) the normalization is usually dropped and the terms "autocorrelation" and "autocovariance" are used interchangeably.

  9. Cross-correlation - Wikipedia

    en.wikipedia.org/wiki/Cross-correlation

    In time series analysis and statistics, the cross-correlation of a pair of random process is the correlation between values of the processes at different times, as a function of the two times. Let ( X t , Y t ) {\displaystyle (X_{t},Y_{t})} be a pair of random processes, and t {\displaystyle t} be any point in time ( t {\displaystyle t} may be ...