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Reference.org
Quasi-likelihood
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<p>In <a href="/facts/Statistics/DNPsKGYU">statistics</a>, quasi-likelihood methods are used to estimate parameters in a statistical model when exact likelihood methods, for example <a href="/facts/Maximum_likelihood/0Yq2dpQD">maximum likelihood</a> estimation, are computationally infeasible. Due to the wrong likelihood being used, quasi-likelihood estimators lose asymptotic efficiency compared to, e.g., maximum likelihood estimators. Under broadly applicable conditions, quasi-likelihood estimators are <a href="/facts/Consistent_estimator/HAKDWYEM">consistent</a> and <a href="/facts/Estimator/CbkjcKvN">asymptotically normal</a>. The asymptotic covariance matrix can be obtained using the so-called <i>sandwich estimator</i>. Examples of quasi-likelihood methods include the <a href="/facts/Generalized_estimating_equations/nGwEyvmy">generalized estimating equations</a> and pairwise likelihood approaches. </p>