Working Paper

Convolution without independence


Susanne M. Schennach

Published Date

23 September 2013


Working Paper (CWP46/13)

Widely used convolutions and deconvolutions techniques traditionally rely on the assumption of independence, an assumption often criticised as being very strong. We observe that independence is, in fact, not necessary for the convolution theorem to hold. Instead, a much weaker notion, known as subindependence, is the appropriate necessary and sufficient condition. We motivate the usefulness of the subindependence concept by showing that it is arguably as week as a conditional mean assumption. We also provide and devise a constructive method to generate pairs of subindependent random variables.