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The geologic time scale is a way of representing deep time based on events that have occurred throughout Earth's history, a time span of about 4.54 ± 0.05 Ga (4.54 billion years). [5] It chronologically organises strata, and subsequently time, by observing fundamental changes in stratigraphy that correspond to major geological or ...
Time series. 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. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily ...
Observations. Between 1901 and 2018, the global mean sea level rose by about 20 cm (7.9 in). More precise data gathered from satellite radar measurements found an increase of 7.5 cm (3.0 in) from 1993 to 2017 (average of 2.9 mm (0.11 in)/yr).
The gradual decay in flow after the peaks reflects diminishing supply from groundwater. A hydrograph is a graph showing the rate of flow ( discharge) versus time past a specific point in a river, channel, or conduit carrying flow. The rate of flow is typically expressed in cubic meters or cubic feet per second (cms or cfs).
Fan chart (time series) In time series analysis, a fan chart is a chart that joins a simple line chart for observed past data, by showing ranges for possible values of future data together with a line showing a central estimate or most likely value for the future outcomes. As predictions become increasingly uncertain the further into the future ...
Seasonality. In time series data, seasonality refers to the trends that occur at specific regular intervals less than a year, such as weekly, monthly, or quarterly. Seasonality may be caused by various factors, such as weather, vacation, and holidays [1] and consists of periodic, repetitive, and generally regular and predictable patterns in the ...
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. It contrasts with the autocorrelation function, which does not control for other lags. This function plays an important role in ...
Seasonal adjustment or deseasonalization is a statistical method for removing the seasonal component of a time series. It is usually done when wanting to analyse the trend, and cyclical deviations from trend, of a time series independently of the seasonal components. Many economic phenomena have seasonal cycles, such as agricultural production ...