tag:crantastic.org,2005:/authors/8625Latest activity for Amandine Pierrot2019-07-29T09:20:42Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/911212019-07-29T09:20:42Z2019-07-29T09:20:42Zclr was upgraded to version 0.1.2<a href="/packages/clr">clr</a> was <span class="action">upgraded</span> to version <a href="/packages/clr/versions/86629">0.1.2</a><br /><h3>Package description:</h3><p>A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) <doi:10.1080/01621459.2012.722900> and (2015) <doi:10.1007/978-3-319-18732-7_3>. The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/834472019-01-11T16:40:39Z2019-01-11T16:40:39Zclr was upgraded to version 0.1.1<a href="/packages/clr">clr</a> was <span class="action">upgraded</span> to version <a href="/packages/clr/versions/79413">0.1.1</a><br /><h3>Package description:</h3><p>A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) <doi:10.1080/01621459.2012.722900> and (2015) <doi:10.1007/978-3-319-18732-7_3>. The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/823282018-12-03T12:20:35Z2018-12-03T12:20:35Zclr was released<a href="/packages/clr">clr</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) <doi:10.1080/01621459.2012.722900> and (2015) <doi:10.1007/978-3-319-18732-7_3>. The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems.</p>crantastic.org