com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess
Class AdditiveModel

java.lang.Object
  com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.SimpleTimeSeries
      com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.AdditiveModel

All Implemented Interfaces:

TimeSeries<java.lang.Integer,java.lang.Double>

public class AdditiveModel
extends SimpleTimeSeries

The additive model of a time series is an additive composite of the trend, seasonality and irregular random components.

 Y[t] = T[t] + S[t] + e[t]
 

Nested Class Summary

Nested classes/interfaces inherited from class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.SimpleTimeSeries

SimpleTimeSeries.Iterator

Nested classes/interfaces inherited from interface com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.TimeSeries

TimeSeries.Entry

Constructor Summary

AdditiveModel(double[] trend, double[] seasonality, double[] randoms)
Construct a univariate time series by adding up the components.

AdditiveModel(double[] trend, double[] seasonality, RandomNumberGenerator rng)
Construct a univariate time series by adding up the components.

Method Summary

Methods inherited from class com.numericalmethod.suanshu.stats.timeseries.univariate.realtime.SimpleTimeSeries

diff, drop, equals, get, hashCode, iterator, lag, lag, size, toArray, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

AdditiveModel

public AdditiveModel(double[] trend,
                     double[] seasonality,
                     double[] randoms)

Construct a univariate time series by adding up the components.

Parameters:

trend - the trend component

seasonality - the seasonality component

randoms - the irregular random component

AdditiveModel

public AdditiveModel(double[] trend,
                     double[] seasonality,
                     RandomNumberGenerator rng)

Construct a univariate time series by adding up the components. The irregular random component is generated using a custom random number generator.

Parameters:

trend - the trend component

seasonality - the seasonality component

rng - a random number generator