Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: On synthetic data with predetermined subject partitioning and cluster
  profiling, and pre-specified categorical variable marginal dependence
  structure   A standard approach for assessing the performance of partition or mixture
models is to create synthetic data sets with a pre-specified clustering
structure, and assess how well the model reveals this structure. A common
format is that subjects are assigned to different clusters, with variable
observations simulated so that subjects within the same cluster have similar
profiles, allowing for some variability. In this manuscript, we consider
observations from nominal, ordinal and interval categorical variables.
Theoretical and empirical results are utilized to explore the dependence
structure between the variables, in relation to the clustering structure for
the subjects. A novel approach is proposed that allows to control the marginal
association or correlation structure of the variables, and to specify exact
correlation values. Practical examples are shown and additional theoretical
results are derived for interval data, commonly observed in cohort studies,
including observations that emulate Single Nucleotide Polymorphisms. We compare
a synthetic dataset to a real one, to demonstrate similarities and differences.

10
The categories of this paper are: q-bio
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
29
The categories of this paper are: funct-an
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
22
The categories of this paper are: chao-dyn
4
The categories of this paper are: cond-mat
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
24
The categories of this paper are: dg-ga