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An iterative algorithm for solving the optimization problem is developed. The estimator is compared to a number of other covariance estimators and is shown to do best, both in simulations and on a real data example. Simulations show that the margin by which the estimator outperforms its competitors tends to increase with dimension.<\/jats:p>","DOI":"10.1214\/07-aoas139","type":"journal-article","created":{"date-parts":[[2008,3,24]],"date-time":"2008-03-24T10:37:02Z","timestamp":1206355022000},"page":"245-263","source":"Crossref","is-referenced-by-count":150,"title":["Sparse estimation of large covariance matrices via a nested Lasso penalty"],"prefix":"10.1214","volume":"2","author":[{"given":"Elizaveta","family":"Levina","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Adam","family":"Rothman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ji","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"108","reference":[{"key":"1","unstructured":"Adam, B., Qu, Y., Davis, J., Ward, M., Clements, M., Cazares, L., Semmes, O., Schellhammer, P., Yasui, Y., Feng, Z. and Wright, G. 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