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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.
EWMA chart. In statistical quality control, the EWMA chart (or exponentially weighted moving average chart) is a type of control chart used to monitor either variables or attributes-type data using the monitored business or industrial process 's entire history of output. [ 1] While other control charts treat rational subgroups of samples ...
Kernel smoother. A kernel smoother is a statistical technique to estimate a real valued function as the weighted average of neighboring observed data. The weight is defined by the kernel, such that closer points are given higher weights. The estimated function is smooth, and the level of smoothness is set by a single parameter.
It is a measure used to evaluate the performance of regression or forecasting models. It is a variant of MAPE in which the mean absolute percent errors is treated as a weighted arithmetic mean. Most commonly the absolute percent errors are weighted by the actuals (e.g. in case of sales forecasting, errors are weighted by sales volume). [3]
Local regression or local polynomial regression, [ 1] also known as moving regression, [ 2] is a generalization of the moving average and polynomial regression. [ 3] Its most common methods, initially developed for scatterplot smoothing, are LOESS ( locally estimated scatterplot smoothing) and LOWESS ( locally weighted scatterplot smoothing ...
The weighted arithmetic mean is similar to an ordinary arithmetic mean (the most common type of average ), except that instead of each of the data points contributing equally to the final average, some data points contribute more than others. The notion of weighted mean plays a role in descriptive statistics and also occurs in a more general ...
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.