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- W3201231753 abstract "An experiment records stimulus and response for a random sample of cases. The relationship between response and stimulus is thought to be linear, the values of the slope and intercept varying by case. From such data, we construct a consistent, asymptotically normal, nonparametric estimator for the joint density of the slope and intercept. Our methodology incorporates the radial projection-slice theorem for the Radon transform, a technique for locally linear nonparametric regression and a tapered Fourier inversion. Computationally, the new density estimator is more feasible than competing nonparametric estimators, one of which is based on moments and the other on minimum distance considerations." @default.
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- W3201231753 date "1996-01-01" @default.
- W3201231753 modified "2023-09-26" @default.
- W3201231753 title "ON NONPARAMETRIC ESTIMATION OF INTERCEPT AND SLOPE DISTRIBUTIONS IN RANDOM" @default.
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