Nonparametric methods for solving the Berkson errors-in-variables problem
It is common, in errors-in-variables problems in regression, to assume that the errors are incurred 'after the experiment', in that the observed value of the explanatory variable is an independent perturbation of its true value. However, if the errors are incurred 'before the experiment' then the true value of the explanatory variable equals a perturbation of its observed value. This is the context of the Berkson model, which is increasingly attracting attention in parametric and semiparametric...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of the Royal Statistical Society Series B|
|01_Delaigle_Nonparametric_methods_for_2006.pdf||330.16 kB||Adobe PDF||Request a copy|
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