tech.nmfin.portfoliooptimization.lai2010.fit

Interface ResamplerModel

All Known Implementing Classes:

SimpleAR1Fit, SimpleGARCHFit

public interface ResamplerModel

Method Summary

Modifier and Type	Method and Description
Matrix	fittedValues() Gets the fitted observations from the model.
static Matrix	fittedValues(OLSResiduals[] residuals) Combines fitted response vectors as columns of a matrix.
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.

Method Detail

fittedValues

Matrix fittedValues()

Gets the fitted observations from the model.

Returns:

the matrix of fitted observations

standarizedInnovations

Matrix standarizedInnovations()

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.

Returns:

the matrix of standardized innovations

sigma2

Matrix sigma2()

Gets the conditional variances of residuals over time.

Returns:

the matrix of conditional residual variances

fittedValues

static Matrix fittedValues(OLSResiduals[] residuals)

Combines fitted response vectors as columns of a matrix.

Parameters:

residuals - one residual-analysis object per response series, all with the same length

Returns:

a read-only matrix with observations in rows and response series in columns