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Nonparametric estimation and symmetry tests for conditional density functions. (English) Zbl 1013.62040
Summary: We suggest two improved methods for conditional density estimation. The first is based on locally fitting a log-linear model, and is in the spirit of recent work on locally parametric techniques in density estimation. The second method is a constrained local polynomial estimator. Both methods always produce non-negative estimators. We propose an algorithm suitable for selecting the two bandwidths for either estimator. We also develop a new bootstrap test for the symmetry of conditional density functions. The proposed methods are illustrated by both simulation and application to a real data set.

MSC:
62G07 Density estimation
62G10 Nonparametric hypothesis testing
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