This paper studies boundary effects of the kernel density estimation and pr
oposes some remedies to the problems. Since the kernel estimate is designed
for estimating a smooth density, it introduces a large bias near the bound
aries where the density is discontinuous. Bandwidth selectors developed for
the kernel estimate that select a small bandwidth to reduce the bias can d
ramatically increase the variation and roughness of the density estimate. I
n this paper, several boundary adjusted procedures for estimating the densi
ty, as well as selecting the bandwidth, are introduced. The proposed proced
ures greatly reduce the boundary effects and is shown that these density es
timates have the same optimal convergence rate as that of the kernel densit
y estimate of a smooth density. Some asymptotic results about the boundary
adjusted procedures are provided. Simulation studies were carried out to ch
eck the empiric performance of the proposed procedures compared to some exi
sting boundary-corrected estimation procedures. In general, simulation resu
lts indicate that for moderate to large sample sizes, the proposed procedur
es reduce the boundary Effects substantially, and are better than comparabl
e existing methods. As an example, we estimate a relevant density connected
with some coal-mining disaster data.