Title :
Nonparametric Estimation of Conditional Distributions
Author :
Györfi, László ; Kohler, Michael
Author_Institution :
Dept. of Comput. Sci. & Inf. Theor., Budapest Univ. of Technol. & Econ.
fDate :
5/1/2007 12:00:00 AM
Abstract :
Estimation of conditional distributions is considered. It is assumed that the conditional distribution is either discrete or that it has a density with respect to the Lebesgue measure. Partitioning estimates of the conditional distribution are constructed and results concerning consistency and rate of convergence of the integrated total variation error of the estimates are presented
Keywords :
convergence; statistical distributions; Lebesgue measure; conditional distribution; convergence; Automation; Convergence; Density measurement; Error correction; Pattern recognition; Power generation economics; Probability distribution; Random variables; Statistical distributions; Statistical learning; Conditional density; Poisson regression; conditional distribution; confidence sets; partitioning estimate; rate of convergence; universal consistency;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2007.894631
