Testing the Order of a Finite Mixture

By Pengfei Li, Jiahua Chen. 2010

82 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/673bf30e0a58e856d4d686e210f0ccb83af3cf55

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Hiroyuki Kasahara
2. Katsumi Shimotsu
3. Pengfei Li
4. Yuejiao Fu
5. Jiahua Chen
6. Xuming He
7. Juan Shen
8. Andrew Sweeting

In Statistics and Probability

1. Hiroyuki Kasahara
2. Katsumi Shimotsu
3. Pengfei Li
4. Yuejiao Fu
5. Jiahua Chen
6. Xuming He
7. Juan Shen
8. Ying Wei

Citations in the corpus

• Testing the Number of Components in Normal Mixture Regression Models (2015, methodology): “The test of Shen and He (2014) has a simpler limiting distribution, but its power is low when the mixing proportion does not depend on covariates.”
• Inference for Subgroup Analysis With a Structured Logistic-Normal Mixture Model (2015, background): “Recently, Chen and Li (2009) and Li and Chen (2010) proposed the so-called EM test that does not rely on the maximized likelihood.”
• Inference on the Order of a Normal Mixture (2012, background): “Li and Chen (2010) developed an expectationmaximization (EM) test for assessing the order of finite mixture models with single-parameter component distributions.”