Before revision:  When the data has compact support, as all empirical applications de facto do, conventional kernel-based density estimators are inapplicable near or at the boundary because of their well known boundary bias.
After revision:  When the underlying distribution has compact support, as all empirical applications de facto do, conventional kernel-based density estimators are inapplicable near or at the boundary because of their well known boundary bias.