Quantile Probability and Statistical Data Modeling

By Emanuel Parzen. 2004

152 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Radiological and Ultrasound Technology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fc033b08a05eaa4cd67b12fe8272e78a5348219a

How researchers see this paper

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

In Management Science and Operations Research

1. Stijn Ferrari
2. Carlos Castro
3. Ivan Mizera
4. Linglong Kong

In Radiological and Ultrasound Technology

1. Stijn Ferrari
2. Carlos Castro
3. Ivan Mizera
4. Linglong Kong

In Statistics and Probability

1. Linglong Kong
2. Stijn Ferrari
3. Carlos Castro
4. Ivan Mizera
5. Richard J. Samworth
6. Chao Gao
7. Roger W. Koenker
8. Richard A. Berk

Citations in the corpus

• Measuring and testing for the systemically important financial institutions (2012, background): “7For a detailed discussion of the properties of quantile functions and proofs, see Parzen (1979, 2004).”
• Quantile tomography: using quantiles with multivariate data (2008, background): “hat 50 is the 0:9-th quantile leads to unambiguous conclusion that about 10% of the results are to be expected beyond, and about 90% below 50. Compared to other statistical uses|for which we refer to Parzen (2004) and the references there|this \descriptive grip" is very palpable, and hard to im”