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java.lang.Object com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.MADecomposition
public class MADecomposition
This class decomposes a time series into the trend, seasonal and stationary random components using the Moving Average Estimation method with symmetric window. That is,
X_{t} = m_{t} + s_{t} + Y_{t}We have
decompose
.
Constructor Summary  

MADecomposition(double[] xt,
double[] MAFilter,
int period)
Decompose a time series into the trend, seasonal and stationary random components using the Moving Average Estimation method. 

MADecomposition(double[] xt,
int period)
Decompose a periodic time series into the seasonal and stationary random components using no MA filter. 

MADecomposition(double[] xt,
int MAOrder,
int period)
Decompose a time series into the trend, seasonal and stationary random components using the default filter. 
Method Summary  

double[] 
getRandom()
Get the estimated seasonal effect of the time series. 
double[] 
getSeasonal()
Get the stationary random component of the time series after the trend and seasonal components are removed. 
double[] 
getTrend()
Get the estimated trend of the time series. 
Methods inherited from class java.lang.Object 

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait 
Constructor Detail 

public MADecomposition(double[] xt, double[] MAFilter, int period)
xt
 a time seriesMAFilter
 the moving average filter to smooth the time seriesperiod
 the period of the time series; if aperiodic, use 1public MADecomposition(double[] xt, int MAOrder, int period)
xt
 a time seriesMAOrder
 the length of the MA filter (automatically increased by 1 for even
MAOrder
)period
 the period of the time series; if aperiodic, use 0public MADecomposition(double[] xt, int period)
xt
 a time seriesperiod
 the period of the time series; if aperiodic, use 0Method Detail 

public double[] getTrend()
public double[] getSeasonal()
public double[] getRandom()


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