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- W2073208705 abstract "We consider the fitting of generalized linear models in which the link function is assumed to be unknown, and propose the following computational method: First, estimate regression coefficients using the canonical link. Then, estimate the link via a kernel smoother, treating the direction in the predictor space determined by the regression coefficients as known. Then reestimate the direction using the estimated link and alternate between these two steps. We show that under fairly general conditions, $n^{1/2}$-consistent estimates of the direction are obtained. A small Monte Carlo study is presented." @default.
- W2073208705 created "2016-06-24" @default.
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- W2073208705 date "1994-12-01" @default.
- W2073208705 modified "2023-10-17" @default.
- W2073208705 title "Adapting for the Missing Link" @default.
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- W2073208705 doi "https://doi.org/10.1214/aos/1176325749" @default.
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