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Conditional Mode: An Approach via Smoothed Quantile Regression
Moda condicional: un enfoque vía regresión cuantílica suavizada
DOI:
https://doi.org/10.15446/rce.v48n3.122634Keywords:
Mode regression, Convolution. (en)Regresión modal, Convolución. (es)
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Recently, it has been proposed to estimate the conditional mode of a response, given a vector of covariates, using a computationally scalable estimator derived from the linear quantile regression model. Alternatively, we propose to estimate the conditional mode by maximizing a smoothed conditional density estimator. This approach offers at least two benefits: computational efficiency and good asymptotic behavior which, in particular, bypasses the curse of dimensionality.
Recientemente, se ha propuesto estimar la moda condicional de una respuesta, dado un vector de covariables, mediante un estimador computacionalmente escalable derivado del modelo de regresión cuantílica lineal. Como alternativa, proponemos estimar la moda condicional maximizando un estimador de densidad condicional suavizada. Este enfoque ofrece al menos dos ventajas: eficiencia computacional y un buen comportamiento asintótico que, en particular, evita la maldición de la dimensionalidad.
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