estimates the background of data.


tries to preserve peaks up to scale σ.

Details and Options

  • EstimatedBackground estimates the background while trying to preserve features of the input list.
  • Input data can be of one of the following forms:
  • {y1,y2,}a list of values
    TimeSeries[]time series object
    EventSeries[]event series object
  • The following options can be given:
  • MethodAutomaticmethod to use
    Padding"Reversed"padding scheme to use
  • EstimatedBackground accepts a Method option. Possible settings are:
  • "MovingAverage"moving-average background estimation
    {"SNIP",r}statistics-sensitive nonlinear iterative peak clipping


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Basic Examples  (2)

Estimate the baseline of a list:

Remove the baseline from original data and visually compare the lists:

Estimate background of a sinusoidal signal:

Scope  (4)

The background is scale dependent; by default, an automatically computed scale is used:

At scale the background is a close estimation of the input data:

Specify a different scale:

Comparison of different scales:

Estimate baseline of a Quantity object:

Estimate baseline of a regularly sampled TimeSeries object:

Estimated baseline of an irregularly sampled TimeSeries object:

Options  (1)

Padding  (1)

The default padding is "Reversed":

Specify a different padding:

Applications  (2)

Estimate and subtract the background from the recent sunspot activity:

Plot data after background subtraction:

Hourly temperature for Chicago in December:

The plot indicates that data contains missing values. Specify MissingDataMethod and estimate the background:

Create the time series of the original data minus the background:

Fit a weakly stationary time series model:

Properties & Relations  (1)

The "MovingAverage" computes the MovingAverage of the padded input:

Introduced in 2014