Class SimpleAR1Fit
- java.lang.Object
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- dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel
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- dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel
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- dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAModel
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- dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARModel
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- tech.nmfin.portfoliooptimization.lai2010.fit.SimpleAR1Fit
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- All Implemented Interfaces:
ResamplerModel
public class SimpleAR1Fit extends VARModel implements ResamplerModel
This class does a quick AR(1) fitting to the time series, essentially treating the returns as independent. A better way to fit the data is to useVARFit
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Constructor Summary
Constructors Constructor Description SimpleAR1Fit(Matrix mts)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description Matrix
fittedValues()
Matrix
sigma2()
Gets the conditional variances of residuals over time.Matrix
standarizedInnovations()
Gets the standarized innovations (normalized by the conditional standard deviation at the time) of the time series.-
Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAModel
conditionalMean, getDemeanedModel, unconditionalMean
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Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel
getVARMA
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Constructor Detail
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SimpleAR1Fit
public SimpleAR1Fit(Matrix mts)
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Method Detail
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fittedValues
public Matrix fittedValues()
- Specified by:
fittedValues
in interfaceResamplerModel
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standarizedInnovations
public Matrix standarizedInnovations()
Description copied from interface:ResamplerModel
Gets the standarized innovations (normalized by the conditional standard deviation at the time) of the time series. Note (haksunli): we should not use instead the non-standarized innovations (have non-unit variances) because when they are scaled by the time dependent standard deviations/variances. We cannot simply shuffle them to get a new time series of innovations.- Specified by:
standarizedInnovations
in interfaceResamplerModel
- Returns:
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sigma2
public Matrix sigma2()
Description copied from interface:ResamplerModel
Gets the conditional variances of residuals over time.- Specified by:
sigma2
in interfaceResamplerModel
- Returns:
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