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- W146599753 abstract "In this paper, I study the estimation of nonlinear models of spatial processes. Generalized estimating equations (GEE) are applied to cross section data with spatial correlations. I use a partial quasi-maximum likelihood estimator (PQMLE) in the …rst step and use a GEE approach in the second step. Given some regularity conditions and assumptions, the asymptotic distribution of the two-step estimator is derived in the framework of M-estimation. I use a probit model and a count data model to demonstrate the GEE procedure. Monte Carlo" @default.
- W146599753 created "2016-06-24" @default.
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- W146599753 date "2012-10-28" @default.
- W146599753 modified "2023-09-23" @default.
- W146599753 title "Estimation of Nonlinear Models in a Quasi-Maximum Likelihood Framework with Spatial Data" @default.
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