Filter

scalation.modeling.forecasting.Filter
trait Filter(y: VectorD)

The Filter trait provides basic time series capabilities for filters. A filter is used to pull out the important information from a time series. Commonly, this involves improving the signal-to-noise ratio, which is often accomplished by using a low-pass filter that remove high frequencies. Such filters are also called smoothers (the smoothed time series has less abrupt changes)

Value parameters

y

the response vector (time series data)

Attributes

Graph
Supertypes
class Object
trait Matchable
class Any
Known subtypes

Members list

Value members

Abstract methods

def smooth(y_: VectorD = ..., a: Double = ...): VectorD

Return a smoothed version of the given time series vector.

Return a smoothed version of the given time series vector.

Value parameters

a

the smoothing parameter

y_

the actual time series values to be smoothed

Attributes