Generalization of the Total Variance Approach to the Different Classes of Structure Functions
Francois Vernotte, David A. Howe
The Total variance approach has been developed for in-creasing the conﬁdence of the estimation of the classical Allan variance (AVAR), particularly for large integration time values. This method is based on a procedure of extension of the original data sequence called the mirror- reﬂection which increases the equivalent degrees of freedom of each Allan variance estimate. Recently, we applied this approach to the Modiﬁed Allan variance (MVAR) and proved that, in this case, an-other procedure of extension of the data sequence should be used: the reﬂection- only extension.
and Howe, D.
Generalization of the Total Variance Approach to the Different Classes of Structure Functions, Proceedings of 2000 EFTF Conference, , US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=920082
(Accessed June 1, 2023)