Inference Functions and Quadratic Score Tests

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Consistent model selection and data‐driven smooth tests for longitudinal data in the estimating equations approach (2009, methodology): “To understand this better, a geometrical interpretation of the QIF from the projection point of view can be found in Lindsay and Qu (2003).”
Building adaptive estimating equations when inverse of covariance estimation is difficult (2003, methodology): “Under regularity conditions, the generalized method-of-moments estimator is consistent, asymptotically normal and asymptotically efficient in the semiparametric model in which the moment conditions are satisfied (Hansen, 1982; Lindsay and Qu, 2002).”
Marginal regression analysis of longitudinal data with time‐dependent covariates: a generalized method‐of‐moments approach (2007, methodology): “This is because, with the independent working correlation, Hi is a diagonal matrix and therefore (see equation (5)) lim N→∞ [Eβ0{Uj.β0/}]=Eβ0 [ T∑ t=1 Hi[tt] @μit.β0/ @βj {yit −μit.β0/} ] =0:”
Optimal sufficient dimension reduction in regressions with categorical predictors (2002, background): “As discussed by Ferguson (1958), Lindsay and Qu (2003), and Shapiro (1986), a well-known choice of Vn is a consistent estimate of the inverse of the asymptotic covariance of √ n(vec(̂)−vec( )).”