# 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