Approximating conditional distribution functions using dimension reduction
Motivated by applications to prediction and forecasting, we suggest methods for approximating the conditional distribution function of a random variable Y given a dependent random d-vector X. The idea is to estimate not the distribution of Y|X, but that of Y|θᵀX, where the unit vector θ is selected so that the approximation is optimal under a least-squares criterion. We show that θ may be estimated root-n consistently. Furthermore, estimation of the conditional distribution function of Y, given...[Show more]
|Collections||ANU Research Publications|
|Source:||Annals of Statistics|
|01_Hall_Approximating_Conditional_2005.pdf||301.42 kB||Adobe PDF|
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