Rolling Regression

Rolling regression is a procedure of estimating regression parameters at a sample interval with constant width that is gradually shifted in time. Regression enables the user to build trajectories of coefficients estimations together with their confidence limits and check hypothesis about constancy of regression equation coefficients in time.

Indicate a sample interval with constant width as a roll. Let one roll contain w observations, then a model of kth rolling regression with the step h looks as follows:

yk=Xk βk+ek

Where:

The total amount of rolls is 

Where T is the total number of observations.

The following operations can be executed for the obtained βk:

See also:

Library of Methods and Models | ISmRollingRegression