On nonparametric estimation of intercept and slope distributions in random coefficient regression
On nonparametric estimation of intercept and slope distributions in random coefficient regression
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 …