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NEWS.md

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pedmod 0.2.5

  • pedmod_profile_nleq() passes on the augmented penalty parameter for the quadratic term and the Lagrangian parameter to auglag() if maxvls_start and minvls_start is passed.
  • A citation is added.

pedmod 0.2.4

  • deal with a deprecated << operator for arma objects in version 11.2.3.

pedmod 0.2.3

  • eval_pedigree_hess is faster.
  • fixed a bug from release 0.2.0 which in extreme settings could cause the C++ code to run forever.
  • deal with a breaking change in RcppArmadillo which could possibly cause issues in this package. See https://stackoverflow.com/a/72533955/5861244
  • better starting values are used by pedmod_profile_prop. It is also possible to pass a bound on the confidence interval using the bound argument.
  • mvndst_grad is added which computes the gradient with respect to the mean and covariance matrix.

pedmod 0.2.2

  • a minor bug fix on Mac when using Apple LLVM version 10.0.0 with R version 4.2.0 and x86_64.

pedmod 0.2.1

  • A hessian approximation of objects from pedigree_ll_terms is added in the eval_pedigree_hess function.
  • pedmod_profile works with object from pedigree_ll_terms_loadings.
  • pedmod_profile_nleq has been added to construct profile likelihood based confidence intervals for general non-linear transformations of the model parameters.
  • An undefined undefined behavior bug has been fixed in the C++ code which possibly effects cases where use_aprx = TRUE but only in very extreme settings.
  • A bug has been fixed in pedmod_profile_prop. minvls_start and maxvls_start were used instead of minvls and maxvls.
  • The code to compute the limits in pedmod_profile and pedmod_profile_prop has been changed. The previous code could give very wrong points for the conf element if a point was computed very far from one of the confidence limits. The issue was caused by using approx in combination with spline and with points with great distance.

pedmod 0.2.0

  • pedigree_ll_terms_loadings is implemented to support models with individual specific covariance scale parameters (e.g. individual specific heritabilities).
  • The minimax tilting method suggested by Botev (2017) (see https://doi.org/10.1111/rssb.12162) is implemented. The method is less numerically stable and thus required more care when implementing. This yield a higher per randomized quasi-Monte Carlo sample cost. Though, the increased cost may be worthwhile for low probability events because of a reduced variance at a fixed number of samples.
  • The vls_scales argument is added which allows the user to use more randomized quasi-Monte Carlo samples for some log likelihood terms. This is useful e.g. when one uses weighted terms.

pedmod 0.1.0

  • First release on CRAN.