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In the statistical analysis of time series, autoregressive–moving-average ( ARMA) models provide a parsimonious description of a (weakly) stationary stochastic process in terms of two polynomials, one for the autoregression (AR) and the second for the moving average (MA). The general ARMA model was described in the 1951 thesis of Peter ...
In statistics, a moving average ( rolling average or running average or moving mean[ 1] or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set. Variations include: simple, cumulative, or weighted forms. Mathematically, a moving average is a type of convolution.
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.
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.
The simple moving average (SMA) is a literal average of prices over time. Taking the example of a 200-day simple moving average, you would add up the closing price of the stock over the past 200 ...
Box–Jenkins method. In time series analysis, the Box–Jenkins method, [ 1] named after the statisticians George Box and Gwilym Jenkins, applies autoregressive moving average (ARMA) or autoregressive integrated moving average (ARIMA) models to find the best fit of a time-series model to past values of a time series .
Due to the central limit theorem (from statistics), the Gaussian can be approximated by several runs of a very simple filter such as the moving average. The simple moving average corresponds to convolution with the constant B-spline (a rectangular pulse). For example, four iterations of a moving average yield a cubic B-spline as a filter window ...
In signal processing, white noise is a random signal having equal intensity at different frequencies, giving it a constant power spectral density. [ 1] The term is used with this or similar meanings in many scientific and technical disciplines, including physics, acoustical engineering, telecommunications, and statistical forecasting.