ResamplerModel (NM DEV API (v1.2.4) by NM)

All Known Implementing Classes:

SimpleAR1Fit, SimpleGARCHFit
```
public interface ResamplerModel
```

Method Summary

All Methods Static Methods Instance Methods Abstract Methods
Modifier and Type	Method	Description
`Matrix`	`fittedValues()`
`static Matrix`	`fittedValues(OLSResiduals[] residuals)`
`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()
```
  - 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:
  - sigma2
```
Matrix sigma2()
```
    Gets the conditional variances of residuals over time.
    
    Returns:
  - fittedValues
```
static Matrix fittedValues(OLSResiduals[] residuals)
```