covariance_mesh, cov_function_mesh,
and make_A documentation.model_options argument to
rspde_lme() function, which allows users to set starting
values for different parameters and also to fix parameters during
estimation.previous_fit argument to
rspde_lme(), which allows users to provide a previously
fitted model as input to obtain starting values for a new fit.cross_validation function to allow for
multiple likelihoods.rspde.intrinsic for stability.rspde.intrinsic.wCRPS and swCRPS scores on
cross_validation.group_predict function, to obtain
predictions on a testing set based on observations on a training
set.stochvol, stochvol.nig,
stochvolln and binomial likelihoods in
cross_validation function.nu.upper.bound to 2 in dimension
1, and keeping the default nu.upper.bound to 4 in dimension
2 in rspde.matern() function.matern.rational() operators for creating
stationary matern operators.spacetime.operators() for creating space-time
models.matern2d.operators() for anisotropic
operators.INLA and inlabru.INLA and inlabru.INLA and inlabru.data argument in predict.rspde_lme has
been changed to newdata.covariance_mesh and
cov_function_mesh methods as functions in the list returned
by objects obtained from matern.operators() and
spde.matern.operators().MetricGraph package.cross_validation function to match the
updates in inlabru.glance and augment methods for
rspde_lme objects.cross_validation function which has several
scoring rules implemented (MSE, CRPS, SCRPS, DSS) based on our
inlabru implementation of the rational SPDE approach.
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