tag:crantastic.org,2005:/authors/6496Latest activity for Marco Nijmeijer2019-05-16T10:21:51Zcrantastic.orgtag:crantastic.org,2005:TimelineEvent/884982019-05-16T10:21:51Z2019-05-16T10:21:51Zlmvar was upgraded to version 1.5.2<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/84132">1.5.2</a><br /><h3>Package description:</h3><p>Runs a linear-like regression with in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/860182019-03-15T09:41:47Z2019-03-15T09:41:47Zlmvar was upgraded to version 1.5.1<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/81800">1.5.1</a><br /><h3>Package description:</h3><p>Runs a linear-like regression with in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/746852018-05-07T12:01:51Z2018-05-07T12:01:51Zlmvar was upgraded to version 1.5.0<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/71295">1.5.0</a><br /><h3>Package description:</h3><p>Runs a linear-like regression with in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/699492018-01-04T13:41:25Z2018-01-04T13:41:25Zlmvar was upgraded to version 1.4.0<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/66831">1.4.0</a><br /><h3>Package description:</h3><p>Runs a linear regression in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/662072017-09-07T17:01:34Z2017-09-07T17:01:34Zlmvar was upgraded to version 1.3.0<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/63327">1.3.0</a><br /><h3>Package description:</h3><p>Runs a linear regression in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/635542017-06-15T15:21:18Z2017-06-15T15:21:18Zlmvar was upgraded to version 1.2.1<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/60786">1.2.1</a><br /><h3>Package description:</h3><p>Runs a linear regression in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/634782017-06-13T16:21:17Z2017-06-13T16:21:17Zlmvar was upgraded to version 1.2.0<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/60710">1.2.0</a><br /><h3>Package description:</h3><p>Runs a linear regression in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/608642017-03-29T12:21:07Z2017-03-29T12:21:07Zlmvar was upgraded to version 1.1.0<a href="/packages/lmvar">lmvar</a> was <span class="action">upgraded</span> to version <a href="/packages/lmvar/versions/58255">1.1.0</a><br /><h3>Package description:</h3><p>Runs a linear regression in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.orgtag:crantastic.org,2005:TimelineEvent/595582017-02-17T14:01:12Z2017-02-17T14:01:12Zlmvar was released<a href="/packages/lmvar">lmvar</a> was <span class="action">released</span><br /><h3>Package description:</h3><p>Runs a linear-like regression with in which both the expected value and the variance can vary per observation. The expected values mu follows the standard linear model mu = X_mu * beta_mu. The standard deviation sigma follows the model log(sigma) = X_sigma * beta_sigma. The package comes with two vignettes: 'Intro' gives an introduction, 'Math' gives mathematical details.</p>crantastic.org