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Determining the number of factors in high-dimensional generalized latent factor models
Y. Chen,
X. Li
Statistics (Twin Cities)
Research output
:
Contribution to journal
›
Article
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peer-review
1
Scopus citations
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Dive into the research topics of 'Determining the number of factors in high-dimensional generalized latent factor models'. Together they form a unique fingerprint.
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Mathematics
Factor Models
80%
Information Criterion
78%
High-dimensional
51%
Error Bounds
38%
Binary Choice
32%
Personality
28%
Questionnaire
26%
Missing Values
25%
Multivariate Data
23%
Linear Model
18%
Count
18%
Evaluate
16%
Sample Size
16%
Simulation Study
15%
Infinity
14%
Generalization
10%
Estimate
9%
Business & Economics
Latent Factor Models
100%
Error Bounds
61%
Missing Values
30%
Sample Size
28%
Binary Choice
27%
Factors
21%
Simulation Study
20%
Questionnaire
19%
Medicine & Life Sciences
Personality
57%
Sample Size
56%
Linear Models
49%
Agriculture & Biology
personality
23%
questionnaires
19%
sampling
7%
methodology
5%