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We propose and analyze an algorithm for the sequential estimation of a conditional quantile in the context of real stochastic codes with vectorvalued inputs. Our algorithm is based on k-nearest… Click to show full abstract
We propose and analyze an algorithm for the sequential estimation of a conditional quantile in the context of real stochastic codes with vectorvalued inputs. Our algorithm is based on k-nearest neighbors smoothing within a Robbins-Monro estimator. We discuss the convergence of the algorithm under some conditions on the stochastic code. We provide non-asymptotic rates of convergence of the mean squared error and we discuss the tuning of the algorithm's parameters.
Keywords:
conditional quantile;
quantile sequential;
sequential estimation;
stochastic codes;
estimation stochastic
Journal Title: Journal of Statistical Theory and Practice
Year Published: 2019
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Journal Title: Journal of Statistical Theory and Practice
Year Published: 2019
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!