tag:crantastic.org,2005:/packages/sparseHessianFDLatest activity for sparseHessianFD2019-03-06T00:23:03Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/854962019-03-06T00:23:03Z2019-03-06T00:23:03ZsparseHessianFD was upgraded to version 0.3.3.4<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/81286">0.3.3.4</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units. See Braun, M. (2017) <doi:10.18637/jss.v082.i10>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/730692018-03-27T17:02:52Z2018-03-27T17:02:52ZsparseHessianFD was upgraded to version 0.3.3.3<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/69751">0.3.3.3</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units. See Braun, M. (2017) <doi:10.18637/jss.v082.i10>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/688542017-11-25T16:22:10Z2017-11-25T16:22:10ZsparseHessianFD was upgraded to version 0.3.3.2<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/65834">0.3.3.2</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units. See Braun, M. (2017) <doi:10.18637/jss.v082.i10>.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/671482017-10-08T04:02:25Z2017-10-08T04:02:25ZsparseHessianFD was upgraded to version 0.3.3.1<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/64229">0.3.3.1</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/616522017-04-19T19:41:45Z2017-04-19T19:41:45ZsparseHessianFD was upgraded to version 0.3.3<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/58969">0.3.3</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/583372017-01-09T16:50:44Z2017-01-09T16:50:44ZsparseHessianFD was upgraded to version 0.3.2<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/55859">0.3.2</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/495382016-03-15T05:41:36Z2016-03-15T05:41:36ZsparseHessianFD was upgraded to version 0.3.0<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/47900">0.3.0</a><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/387932015-02-04T18:31:45Z2015-02-04T18:31:45ZsparseHessianFD was upgraded to version 0.2.0<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">upgraded</span> to version <a href="/packages/sparseHessianFD/versions/38614">0.2.0</a><br /><h3>Package description:</h3><p>Computes Hessian of a scalar-valued function, and returns it in sparse Matrix format, using ACM TOMS Algorithm 636. The user must supply the objective function, the gradient, and the row and column indices of the non-zero elements of the lower triangle of the Hessian (i.e., the sparsity structure must be known in advance). The algorithm exploits this sparsity, so Hessians can be computed quickly even when the number of arguments to the objective functions is large. This package is intended to be useful for numeric optimization (e.g., with the trustOptim package) or in simulation (e.g., the sparseMVN package). The underlying algorithm is ACM TOMS Algorithm 636, written by Coleman, Garbow and More (ACM Transactions on Mathematical Software, 11:4, Dec. 1985).</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/272132012-11-26T18:32:23Z2012-11-26T18:32:23ZsparseHessianFD was released<a href="/packages/sparseHessianFD">sparseHessianFD</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Estimates Hessian of a scalar-valued function, and returns it in a sparse Matrix format. The sparsity pattern must be known in advance. The algorithm is especially efficient for hierarchical models with a large number of heterogeneous units. See Braun, M. (2017) <doi:10.18637/jss.v082.i10>.</p>crantastic.org