tag:crantastic.org,2005:/authors/5370Latest activity for Bo Peng2017-04-18T08:01:33Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/615842017-04-18T08:01:33Z2017-04-18T08:01:33ZQICD was upgraded to version 1.2.0<a href="/packages/QICD">QICD</a> was <span class="action">upgraded</span> to version <a href="/packages/QICD/versions/58901">1.2.0</a><br /><h3>Package description:</h3><p>Extremely fast algorithm "QICD", Iterative Coordinate Descent Algorithm for High-dimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate descent algorithm in the inner iteration with the majorization minimization step in the outside step. For each inner univariate minimization problem, we only need to compute a one-dimensional weighted median, which ensures fast computation. Tuning parameter selection is based on two different method: the cross validation and BIC for quantile regression model. Details are described in Peng,B and Wang,L. (2015) <DOI:10.1080/10618600.2014.913516>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/516202016-05-30T04:41:02Z2016-05-30T04:41:02ZQICD was upgraded to version 1.1.1<a href="/packages/QICD">QICD</a> was <span class="action">upgraded</span> to version <a href="/packages/QICD/versions/49855">1.1.1</a><br /><h3>Package description:</h3><p>Extremely fast algorithm "QICD", Iterative Coordinate Descent Algorithm for High-dimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate descent algorithm in the inner iteration with the majorization minimization step in the outside step. For each inner univariate minimization problem, we only need to compute a one-dimensional weighted median, which ensures fast computation. Tuning parameter selection is based on two different method: the cross validation and BIC for quantile regression model. Details are described in the Peng,B and Wang,L. (2015) linked to via the URL below with <DOI:10.1080/10618600.2014.913516>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/477272016-02-29T22:52:14Z2016-02-29T22:52:14ZQICD was released<a href="/packages/QICD">QICD</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Extremely fast algorithm "QICD", Iterative Coordinate Descent Algorithm for High-dimensional Nonconvex Penalized Quantile Regression. This algorithm combines the coordinate descent algorithm in the inner iteration with the majorization minimization step in the outside step. For each inner univariate minimization problem, we only need to compute a one-dimensional weighted median, which ensures fast computation. Tuning parameter selection is based on two different method: the cross validation and BIC for quantile regression model. Details are described in Peng,B and Wang,L. (2015) <DOI:10.1080/10618600.2014.913516>.</p>crantastic.org