Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Kernel density estimation of a multidimensional efficiency profile   Kernel density estimation is a convenient way to estimate the probability
density of a distribution given the sample of data points. However, it has
certain drawbacks: proper description of the density using narrow kernels needs
large data samples, whereas if the kernel width is large, boundaries and narrow
structures tend to be smeared. Here, an approach to correct for such effects,
is proposed that uses an approximate density to describe narrow structures and
boundaries. The approach is shown to be well suited for the description of the
efficiency shape over a multidimensional phase space in a typical particle
physics analysis. An example is given for the five-dimensional phase space of
the $\Lambda_b^0\to D^0p\pi$ decay.

32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
7
The categories of this paper are: hep-th
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
11
The categories of this paper are: hep-lat
24
The categories of this paper are: dg-ga
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
2
The categories of this paper are: math
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
36
The categories of this paper are: cmp-lg