Smoothing

This page describes routines that deal with smoothing data.

Method: Hodrick Prescott Filter#

Description#

Return a matrix that has been smoothed column-wise using the Hodrick Prescott filter. In other words, the HP filter extracts the trend component from a time series. Our implementation of the filter here makes two passes, forward and backward.

$$\large min_{\tau}(\sum_{t=1}^T\left(y_t - \tau_t\right)^2 + \lambda \sum_{t=2}^{T-1}\left((\tau_{t+1} - \tau_t) - (\tau_t - \tau_{t-1})\right)^2)$$

[1] voxeu.org

[2] bis.org

Returns#

• Smoothed matrix. I.e. a matrix with trend components, cyclical components are ignored.

Method: Moving Average#

Description#

Return a matrix that has been smoothed column-wise using a simple moving average.

Returns#

• Smoothed matrix.

Method: Polynomial#

Description#

Return a matrix that has been smoothed column-wise. The method fits a polynomial of a user specified order, decomposes the vector into trend and cycle components but only returns the trend component.

Returns#

• Smoothed matrix.