Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How to detect outliers in data envelopment analysis by Kourosh and Arash
  method   One of the concerns about using non-parametric estimators such as Data
Envelopment Analysis (DEA), is the presence of outliers. There are a good
number of studies that mention this assessment in the literature of DEA,
however, there is no clear definition to identify what outliers are in DEA.
Moreover, most of the studies have used additional procedures which have high
computational complexities. This paper proposes a suitable definition to
identify outliers as well as a simple methodology to illustrate how DEA, by
using Kourosh and Arash Method (KAM), is easily able to detect outliers without
using additional technologies and their computational complexities. The
methodology of detecting outliers by KAM is represented with an example which
was used in previous research to depict DEA's weakness of detecting outliers.
The results clearly reject this claim that DEA is not able to detect outliers.

29
The categories of this paper are: funct-an
0
The categories of this paper are: hep-ph
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys