Nothing
C++
memory issue in predict.spAbund()
that could result in crashes under certain situations.svcAbund()
to now work with Poisson and negative binomial families. Note that the function now defaults to use family = 'Poisson'
, which differs from the previous implementation when only family = 'Gaussian'
was supported. This switch was done to maintain consistency with other spAbundance model-fitting functions. msNMix()
. n.batch
, batch.length
, n.samples
, n.burn
, n.thin
, n.chains
) are specified in a way that leads to a non-integer value. In such situations, models would previously run and return without an error, but sometimes the last posterior sample in any given chain could have widely inaccurate values, or values that prevented subsequent functions from working. Thanks to Wendy Leuenberger for bringing this to my attention. independent.betas
tag into the priors
list for certain multi-species model types to allow for specifying an independent prior on the species-specific effects as opposed to treating species-specific effects as random effects. This can be useful under certain circumstances when the distribution of effects across species may not be adequately represented by a Gaussian distribution. This tag is available for the following functions: lfMsAbund
(Gaussian only), sfMsAbund
(Gaussian only), and svcMsAbund
.lfMsAbund
). waicAbund()
that prevented it from working with svcMsAbund
models.neonDWP
data set after NEON announced an error in some of the bird point count data (more information here. Also updated the associated vignette that uses these data.msAbund()
function to make it compatible with spOccupancy::updateMCMC()
, which allows for picking up a model run where it left off instead of having to restart the MCMC from scratch. I am planning to allow this functionality for all model fitting functions in spAbundance
in a future version.spAbundance
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