Asymptotics for the likelihood ratio test in a two-component normal mixture model

By Xin Liu, Yongzhao Shao. 2004

55 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Mathematical Physics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/94a3dd2fdd8c069d1066f15934efaf06e98b589e

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. Pengfei Li
2. Jiahua Chen
3. Hiroyuki Kasahara
4. Katsumi Shimotsu
5. Andrew Sweeting
6. Yuejiao Fu
7. Abbas Khalili

In Mathematical Physics

1. Jiahua Chen
2. Pengfei Li

In Statistics and Probability

1. Pengfei Li
2. Jiahua Chen
3. Hiroyuki Kasahara
4. Katsumi Shimotsu
5. Yuejiao Fu
6. Andrew Sweeting

Citations in the corpus

• Hypothesis test for normal mixture models: The EM approach (2009, background): “In Hartigan (1985), Liu, Pasarica and Shao (2003) and Liu and Shao (2004), the likelihood ratio statistic is shown to diverge to infinity as the sample size increases, which forces most researchers to restrict the mixing parameter (θ) into some compact space.”