First inverse moment of a generalized quadratic form

Bengt Lindoff

Research output: Contribution to journalArticlepeer-review


In this paper an approximate expression for the first inverse moment sf(1 - lambda) Sigma(k=1)(t) lambda(t-k)phi(k)phi(k)(T) + lambda(t) (1 - lambda)P-0(i-1), where phi(k) is a Gaussian stationary vector process is derived. This generalized quadratic form is the estimate of the information matrix when using the Recursive Least Squares (RLS) algorithm with forgetting factor. This estimator is commonly used when estimating parameters in time-varying linear stochastic systems. (C) 1998 Elsevier Science B.V. All rights reserved.
Original languageEnglish
Pages (from-to)363-370
JournalStatistics and Probability Letters
Issue number4
Publication statusPublished - 1998

Subject classification (UKÄ)

  • Probability Theory and Statistics


Dive into the research topics of 'First inverse moment of a generalized quadratic form'. Together they form a unique fingerprint.

Cite this