✦ LIBER ✦

Sample Covariance Matrix for Random Vectors with Heavy Tails

✍ Scribed by Mark M. Meerschaert; Hans-Peter Scheffler

Book ID: 110410294
Publisher: Springer US
Year: 1999
Tongue: English
Weight: 618 KB
Volume: 12
Category: Article
ISSN: 0894-9840
DOI: 10.1023/a:1021688101621

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Moment Estimator for Random Vectors with

Moment Estimator for Random Vectors with Heavy Tails

✍ Mark M. Meerschaert; Hans-Peter Scheffler 📂 Article 📅 1999 🏛 Elsevier Science 🌐 English ⚖ 147 KB

If a set of independent, identically distributed random vectors has heavy tails, so that the covariance matrix does not exist, there is no reason to expect that the sample covariance matrix conveys useful information. On the contrary, this paper shows that the eigenvalues and eigenvectors of the sam

Vector random fields with compactly supp

Vector random fields with compactly supported covariance matrix functions

✍ Juan Du; Chunsheng Ma 📂 Article 📅 2013 🏛 Elsevier Science 🌐 English ⚖ 286 KB

Covariance matrix estimation for CFAR de

Covariance matrix estimation for CFAR detection in correlated heavy tailed clutter

✍ Fulvio Gini; Maria Greco 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 349 KB

Effect of truncation on large deviations

Effect of truncation on large deviations for heavy-tailed random vectors

✍ Arijit Chakrabarty 📂 Article 📅 2012 🏛 Elsevier Science 🌐 English ⚖ 309 KB

A law of the iterated logarithm for heav

A law of the iterated logarithm for heavy-tailed random vectors

✍ Hans-Peter Scheffler 📂 Article 📅 2000 🏛 Springer 🌐 English ⚖ 118 KB

A local limit theorem for random walk ma

A local limit theorem for random walk maxima with heavy tails

✍ Søren Asmussen; Vladimir Kalashnikov; Dimitrios Konstantinides; Claudia Klüppelb 📂 Article 📅 2002 🏛 Elsevier Science 🌐 English ⚖ 104 KB