… Modal regression estimates the local modes of the distribution of Y given X = x, instead of
the mean, as in the usual regression sense, and can hence reveal important structure …

… In Section 3, we propose a nonparametric varying coefficient modal regression. A Monte
Carlo simulation study and a real data application are conducted in Section 4 to illustrate the …

… regression (MCCR), our study reveals that MCCR with a tending-to-zero scale parameter
is essentially modal regression. We show that the nonparametric modal regression problem …

… existing research on modal regression when X … modal regression typically results in
misleading inference. We tackle this important problem in our study. We propose two nonparametric …

… regression and nonparametric median regression. We propose to use local polynomial
regression to estimate the nonparametric modal regression. … the nonparametric modal regression …

… As usual, a nonparametric M-type of regression will be more efficient than least-squares-based
nonparametric regression when there are outliers or the error distribution has a heavy tail…

… This following contains proofs of key results in the paper “Nonparametric Modal Regression”.
For clarity, we keep the numbering for the lemmas and theorems consistent with those in …

… Since the nonparametric model without covariates has an infinite number of mixtures (and …
normal linear regression we aim to reduce the variance; with nonparametric regression we …

… modeling can also be based on yet another measure of location—the mode. The key
input of the local modal regression estimating the conditional mode function urn:x-wiley:19395108:…

… However, the role of bandwidth h (control mode) is different from that in nonparametric
regression (control smoothness). According to Yao et al. (2012), the choice of kernel function is …