fmesher::fm_collect() meshes to
inla.spde2.pcmatern() and inla.spde2.matern().tan.pioff)HKprocess is removedinla.group.cvcontrol.modeA.localcontrol.modeinla.mdata-objects in inla.stack (experimental)exppower (experimental)iidkdgroup cv vignetteplotrgeneric or rprioroccupancybetabinomialiidkd from 20 to 24betabinomialtolerance.stepcgeneric.h in cache-macrosplot(..., plot.opt.trace=TRUE) plotmgammainla.knmodelsstochvollnbarrier_globalrpriorgcpofl changesMatrixModels moved to Importsinla.spyexperimental status of many likelihoods and model
componentsscopytpoissonrcpoisson and flcontrol.vb$f.enable.limit to limit
maximum dimension of vb-corrections (which is multiplied with
replicates and group)gev and cgecscopy (experimental)R (experimental, see rprior)group-cvggaussian and ggaussianSreadlink on older MacOSselection is usedinla.call="submit"copystdgaussian (where the precision is fixed to be 1)nzPoisson (for Poisson without zero's)safe=TRUE)control.inla=list(b.strategy="keep") is a new default.control.compute=list(q=TRUE) for the default modefmesher package. By default, the new methods are used
silently instead of the old fmesher standalone binary, and are meant to produce
the same meshes etc as before. During a transition period, one can switch between
the two code bases, as well as turn on informative deprecation warnings
that point to which fmesher R function replaces the existing ones.
See https://inlabru-org.github.io/fmesher/articles/inla_conversion.html
for more details.cdf=.control.expert) for R-4.3.inla.reruninla.rerun23.06.12 fixedinla.setOption-options: mkl, blas.num.threads, vecLib, vecLibPath and CYGWINfbesagcontrol.compute=list(save.memory=FALSE|TRUE) for
more aggressive savingsgcporesult$misc$warningscopyscopy model added (experimental)hessian.correct.skewness.only in control.inlaoffset()
and offset= in the output, compared with
mode='classic'inla.dryrunINLAspacetime functions in barrier.Rinla.dryrun (experimental)cgenericmodel="slm" (thx to RB and VGB)family="nbinom" and "bell"inla.binary.install()rgeneric is updatedinla.posterior.samplecontrol.mode=list(..., fixed=TRUE)rgeos dependencyrgdal dependencycclogloginla.group.cvsafe-mode improved in the inla()-callmodel="fgn"model="binomial" and logit-linkmodel="iidkd"cgeneric-related)inla.cpo, etc.safe, verbose' and keep to optionscontrol.compute=list(residuals=TRUE) provide expected deviance
residuals, but it is experimental for the momentkronecker()weibullcure-model is removed as its covered by the new
cure-model.model="copy"fmesher, the program which do the mesh-stuffcennbinomial2 (experimental)gaussianjw (experimental)inla.group.cv (experimental)Predictor and APredictor in lincomb for
experimental modespde2 modelsgcpo with singular covariance matricesf.enable.limit work the replications and groupsvb variance correction (experimental code)inla.posterior.sample.evalgcpoinla.as.dgTMatrix()inla.as.dgTMatrix()rgenericVersion_22.07.15Version_22.07.15gcpo-outputmode in the output summary is back.gev is disabled, using bgev insteadgcpo-featurestupid-searchsmart-optimizationtheta-correction for gcpo computationsgcpo-handling of singular cases. group.size=-1 now
gives the CPO.strategy="laplace"
which has been broken
from version 22.02.16 (ok in 22.01.25).mode in summary output is not longer computed
for some densities (like for mixtures and non-linear
transformation), as its pretty expensive to do so accurately.
It is then shown as NA. This might be fixed later.cgenericcgeneric, see vignetteexperimental modeOption safe=TRUE is now default
Code cleanup
Code optimization for TACUS
Nested parallelism is now enabled on Windows
gcpo and safe=T fixedA-matrix in gcpoBetter TAUCS performance: improved storage scheme and new code tp allow for linear solves with many rhs.
gcpo-improvement. The default is now group.size=1,
and it acts like cpo.
Fixed an issue for propagation an error from the cpo-calculations
Various smaller changes
New options for the group-cpo feature.
Fixed CRAN-check issues.
VB correction for experimental mode do now include nodes from all model components, not only the short ones and fixed effects.
New group-cpo feature, very experimental at the moment (internal use only).
Parts of the VB code has been improved for simplicity and speed.
inla.call="remote" now use zstd for
parallel compression, meaning that zstd must be
available on both sides.
PARDISO license help and startup msg has been disabled.
Minor fixes, code improvements and cleanup
New feature inla.cgeneric.q
New and updated PARDISO library
Code improvements and cleanup
knmodelsAdded graph$cc$mean to help defining intercepts for
disconnected regions.
Can now define the license key for PARDISO directly as
inla.setOption(pardiso.license="<KEY>")
Print total RAM in Gb in the inla-program output, for easier debugging of these problems.
Using inla.call="remote" will now return error code that can be
controlled by try, so that r=try(inla(..., inla.call="remote"))
should work as intended.
Add a refine step for parallel.linesearch, so if this is
enabled, then it will do a restart at the end with this option
disabled.
Minor changes when option safe is enabled.
Fixed regression error with plot(result, plot.prior=TRUE)
Fixed a regression error from version 21.12.21 which expanded some variables incorrect.
Option safe in function inla
Minor bug fixes
NAN and INFmatern2d modelcgeneric for WindowsA cgeneric interface
like rgeneric but with C-code.
This is for internal testing only.
Various code improvements and minor fixes
Allow for probit cdf in likelihood model pom
Various code improvements
powerprobit. Not completely done yet.Option for parallel linesearch has been renamed into
parallel.linesearch in control.inla.
This is fix for a build-error in the Windows binary for
version 21.11.14
Various minor internal code changes and improvements
Parallel linesearch implemented, see option
bfgs.version in control.inla. This option is highly
experimental at the moment and work in progress, and should
not be used.
Change default settings for family="tweedie"
Implemented an adaptive parallel/serial version of Qx
Improved perforance for parallel linear solve with PARDISO
Use stable Legendre polynomial evaluation for spherical covariances
Add support for Fedora Linux 35
Fixed dic.sat when all response are NA
Various internal code changes and improvements
New experimental feature lp.scale. No good documentation yet, but
that will come soon.
Robustify inla.iidkd.sample function for numerical singular matrices
Corrected inla.stack.join handling of factor variables that in some
cases converted variables to/from factors unintentionally.
inla.mode="experimental" got its fitted values back.
Better special number
New option to inla.iidkd.sample
iidkd which use a different
parameterisation than iid3d and similar ones.int.strategy="user" with
inla.mode="experimental"inla.mode="experimental"scale to family="xbinomial"If control.predictor=list(compute=TRUE) then the
marginal densities for the linear predictor and fitted values are
computed, but the new default is that only the summary statistics
are returned not the marginal densities. This is because the
storage requirement for the marginals can be substantial. The
marginal densities can be returned setting
control.compute=list(return.marginals.predictor=TRUE)
The argument control.results are removed as it was
not really in use.
The new default value for b.strategy is
b.strategy="skip". See ?control.inla for details
New option inla.timeout, similar to
fmesher.timeout; see ?inla.setOption
CPO-marginals are returned in when
control.compute=list(config=TRUE)
There is a change how a (numerical) singular constraint is treated, hopefully this new way is more robust.
New option inla.mode, which define how to arrange the
internal model formulation. One of "classic",
"twostage" and "experimental". The default is
"classic", which is unchanged behaviour compared for
earlier versions. The other two are highly experimental for the
moment. See ?inla
Massive code clean-up and some minor fixes.
Added support for Mac M1 (native build with R-4.1)
New twostage options (highly experimental)
Massive code overhaul
Various minor fixes
Mac only: Added optional path to vecLib
BLAS and LAPACK libraries.
Adding argument .special to inla.surv-object.
Some code improvement
Mac only: Link with vecLib BLAS and LAPACK libraries
by default. Turn off with inla.setOption(vecLib=FALSE).
Adding an experimental improvement
for strategy=simplified.laplace (not enabled by default)
Some code improvement
New family stochvolsn
New family cenpoisson2
Improve robustness for survival models
General code improvement
inla.jp; see help-page for details.New family gompertz
inla.binary.install() now do md5-checksum check
Code optimization for barrier models
family=tweedieinla.binary.install() can now also run
non-interactive
Internal code changes
Added family logperiodogram back in
Added new family agaussian
Improved initial values for x
Improved computations for saturated likelihood
Various minor code cleanup
Default strategy is now simplified.laplace
for smaller models (< 5000 nodes) and adaptive for larger ones
Minor bug-fixes
coxph for large dataFamily fmri
Speed improvements for family tweedie
New family tweedie
Optimization work, code improvement and maintenance
Added a new experimental feature for running PARDISO in parallel
Various minor fixes and improvements
Added new section to the vignette about rgeneric
Option optimize in inla.rgeneric.define
Cleanup in some output format.
Various internal changes.
rgeneric.New family gammajw
Fixed an OpenMP deadlock case, using rgeneric
PARDISO version 7 is included for Mac and Linux.
Improved paralellism and nested paralellism
Speedup improvements, especially for models with many constraints.
Improved default plot(result). Argument
cex=.. will now work
New shorthand feature in inla.posterior.sample.eval
for extracing model components from samples
Added fmesher.timeout option, see ?inla.setOption
Using a non-zero seed in inla.posterior.sample will
now force serial computations.
A lot of internal code cleanup and improvements
New likelihood poisson.special1
Minor code cleanup
Minor changes in code/doc to adapt to R-4.0
Likelihood model sn is redone.
Various minor changes.
Model iid added to possible models
for the baseline hazard in the Cox-ph model
Likelihood models sn and sn2 have been
replaced with a new version sn. The parameterisation is
different and now done correct.
The likelihood models sn and sn2
are now disabled. They need a rewrite to be done right.
For Linux, then build so-libraries are loaded before the
system ones. This behaviour can be reverted by setting the
environment variable INLA_NATIVE_LD_LIBRARY_PATH.
Dimension for CCD integration have been increased from 38 to 52.
Default prior for the intercept and the skewness in the
skew-normal link have changed.
Various minor changes
-tnum.threads="A" now means
num.threads="A:1"There is a minor change in inla.qsample and inla.posterior.sample.
If argument seed!=0 then serial mode is now forced.
Earlier, an error would be raised if parallel mode was also requested.
Argument remove.names in control.fixed
Bug-fixes for nested parallism
Some optimization improvement
Some minor fixes in the install
Linux builds now link with PARDISO version 7 (beta)
MKL is now default for both Mac and Linux.
If this cause any issues, revert back by setting
inla.setOption(mkl=FALSE).
As of today, the TAUCS library does not play
well with MKL on Mac for some reason, and this is
silent accounted for.
It is possible to bypass the internal check,
and if that becomes in issue, just define
mkl=FALSE as above.
Updated some install scripts
Code is prepared for nested parallism, which most gain obtained when using the PARDISO library
Argument num.threads is now in the format A:B,
where A threads for the outer layer and B threads for the inner
layer. And this applies for several functions.
The speed have improved, mostly when using the PARDISO library. Hopefully, nothing is broken.
likelihood beta now allow for cencoring near 0 and 1,
see inla.doc("beta", section="likelihood")
Default value for control.inla$h is now 0.005, which
replace the previous value of 0.01. We might change this later,
but we have enough experience to know that 0.01 is slightly to
large.
control.inla$optimise.strategy="smart" is now
default. By construction, this should be both faster and more
robust. Using "plain" reverts back the old behaviour.
control.inla$use.directions=TRUE is now default. This option
estimate numerical gradients/Hessian in directions with
more change than for coordinate-wise directions.
control.inla=list(use.directions=TRUE/FALSE)New experimental optimise strategy
control.inla=list(optmise.strategy="smart"
that is hopefully faster and as safe as the default one. Maybe
even more safe and robust.
More work on the nested paralellism
jemallocOption control.inla$lincomb.derived.only is now disabled.
Testing nested parallelism openmp.nested with
num.threads="A,B". Work in progress
plot(result) will now produce a plot of the
CPO/PIT for each likelihood family (if available), instead
of a joint plot as earlier.
New vignette about jmarginal
Added new likelihood models zeroinflatedcenpoisson0
and zeroinflatedcenpoisson1
Link-model sn is updated, as well as the
PC-prior for the skewness therein, and the added intercept model.
Revised the PIT calculations for family cenpoisson
Code rewrite to (try to) prevent Inf for DIC calculations
Minor fixed in inla.binary.install
Packages mpoly and symmoments are
added to the Suggests-list.
Added info about inla.prune() to the
startup message
More features for jmarginal added
Build-scripts fixes
Fix for a rare fmesher issue
Improved the code for the DIC calculations to make them more stable
Some improvment in the PC-prior for the SN-link
inla.link.sn to vectorise over argument
a as sn-package do not do that properly itself.family=bGEVgitAdded Qprior.diag to the output when config=TRUE.
The off-diagonals of this matrix are the same as Q in the
same configuration, so only the diagonal of Qprior
is stored.
Added some internal experimental code
PARDISO interface: internal check added
Fixed an wrong assert with family=bgev
For the intslope-model: made all gamma's
default fixed to 1, so its similar in style the copy-feature.
Added argument constr it inla.rjmarginal
Added argument ask to function inla.prune
Argument cyclic=TRUE in f() should not set
constr=FALSE when default is constr=TRUE
Change the scale.model=TRUE code for RW1/RW2 so the
scaling for the continous case is the same as for the discrete
case when the locations are eqvidistant.
Disable link sslogit
besag2plot(r,plot.prior=TRUE) for some priorsRemove the experimental status of inla.posterior.sample.eval
Added function inla.prune which will remove binaries
not supported by the running OS, to reduce the size of the
package.
Added method summary and print to class
inla.jmarginal
Add check for NA/NaN/Inf in mesh creation input
ocations
Make sure that skewness is not to high in inla.posterior.sample
Added new argument tag to inla.coxph
inla.rjmarginal.eval, to evaluate samples from a join
approximations
Names of samples are now "sample:1", "sample:2", and should be coherent over all functions. Similar, their contents, its like "x:1", "x:2", etc.
Fixed a bug setting prior for the log baseline hazard in inla.coxph
result$mode$x is written out in the
case where nhyper=0 and num_threads>1Added link loga. Not yet documented.
First try on a new feature to more easily approximate
the joint marginal for a subset of the latent field. This is a new
option selection and corresponding inla.rjmarginal()
to sample from it.
Added check that model="linear" is not used with
replicate or group, which is not intention.
MCMC mode is now disabled
Skewness correction is now back as default, in
inla.posterior.sample()
Added family xbinomial that allow non-integer
response.
Likelihood model bgev add (not yet complete), and was
renamed from the experimental likelihood model gev2.
If inla.call="remote" is set,
then INLA:::inla.call.builtin() is used
if inla.qinv() and/or inla.qsolve() are
used while constructing the model.
jointdataCD4.rds in exampledata/Added option b.strategy in control.inla to
control what to do with the linear term when the cmin option is
in effect
Added in-interval observed event in inla.surv
Added dplyr as suggested package as
dplyr::bind_rows can replace
INLA::inla.rbind.data.frames
Added argument E, or log(offset), to
likelihood gammacount, so its equal to family poisson
for alpha=1.
Minor changes
Added a check that discrete observations are indeed integers, like for Poisson, Binomial, etc
The function inla.binary.install is now exported.
Added new likelihood family, xpoisson, which allows
continous response: see the documentation for details (and note
the error-check now done for discrete observations)
Added new likelihood dgp (discrete generalized Pareto)
Code clean-up (contpoisson and qcontpoisson)
Made inla.pardiso.check() a bit more informative if
there is an error.
inla.posterior.sample and
inla.coxphNA data in the family gev2pc.gevtail prior.inla.posterior.sample back to the old
version, the new experimental version is available as
INLA:::inla.posterior.sample.newEpil data-set, y[31] should be
23 not 21.Updated the vignette about the multinomial distribution
New experimental windows binary built with
x86_64-w64-mingw32-gcc, version 7.3, and linked with the
pardiso library. Its stored in bin/windows/experimental
Updated inla.qreordering and updated leuk-demo.R
example file (and the corresponding zip-file).
qgamma to speedup
Gamma quantile regressionAdded a scaling constant for the precision parameter in the
qkumar likelihood (to avoid instabilities). See updated
documentation for details.
inla.posterior.sample now correct for possible skewness
by default: see ?inla.posterior.sample for details.
betabinomialnagp, have changed to pc.gevtail, and the name change
from shape to tail. It is now required to define a
interval for the tail parameter, similar to pc.gevtail.loggamma-functionbarrier.R updated (minor fix and code edits)nmixnb likelihood.inla.posterior.sample.eval
if present.INLA:::inla.binary.install() is a new interactive tool
to install alternative Linux builds.sn for binary data,
with its PC-priorAdded robit link model.
Improved the stability of the saturated deviance calculations
Fixed INLA:::inla.is.list.of.lists to cover the
case where the arguments are a list of named lists
New (experimental) likelihood: gev2
Fixed, again, an issue with (parallel) PARDISO and many linear combinations.
Minor code changes in doc.R
Removed must-be-enabled warnings in some surival models, from Oct 25 2017
Added PC-prior for the Weibull likelihood models. The prior
is derived
for variant = 1, which is the good parameterisation.
Added missing to.theta and from.theta
functions in likelihoods sn and sn2
Fix some documentation in marginal.R (refering to the
obsolete function inla.marginal.transform)
Fixed an issue with (parallel) PARDISO and many linear combinations.
StagedInstall:no to work around
installation problems for MacOS and R-3.6short.summary will use a version of
summary with less output, maybe more suitable for
Markdown documents.Added exampledata directory for various example datasets
Code cleanup and improved some input-error checking.
model="rgeneric" and model="dmatern".
Most notably with option openmp.strategy="pardiso.parallel".int.design="user.expert"int.strategy="user.expert", see the vignette
about user-defined integration points.cpo and po results in inla.merge()dmaternmu is zero for rgenericinla.qsamplenhrs for inla.qsolve for PARDISOinla.qsample with
selection-argument.family = "normal" which is now
translated to family = "gaussian" internally.inla.mergeSimplied print.inla output
New method merge and function inla.merge,
for merging inla-objects
Store control.family after processing, in the
result$.args argument, not just the calling value.
New parameter for Gaussian likelihood: Fixed offset in the variance.
Updated envir definition in the rgeneric
documentation and examples.
Removed testing code for likelihood model testbinomial1
Added new likelihood gamma.surv
Cleaned up the use of temporary dir and files
General code clean-up
nmix and nmixnb from 10 to 15New models, loggamma and mloggamma
in mix.
Minor changes in some build scripts.
mkl in inla.setOption() to chose
MKL-buildt binaries.intslopecontrol.mix interface and codenbinomial2inla.priors.usedinlaNew latent model: dmatern
Improved the numerics for computing the scaling of the RW1 and RW2 models.
New option control.inla=list(tolerance.step=), to
control the RMS of the step-size for the inner optimization.
Changed, slightly, the initial values for the exponent in the Weibull likelihood models, to a value close to zero instead of zero.
New vignette about how to deal with multinomial data.
Added option verbose to
inla.qsample() and inla.posterior.sample()
selection in inla.posterior.sample
and inla.qsample.num.threads in inla.qinv()inla.qinv(), inla.qsample() and
inla.posterior.sample()New example added to inla.posterior.sample()
Slight changes in the default print, and
summary for an inla-object
Fixed the issue when lincomb.derived.only=FALSE and
then using inla.posterior.sample()
Added 32-bit builds for windows (upon request)
Added function inla.posterior.sample.eval()
Added new function inla.pardiso.check()
Added COPYRIGHTS file
Separated the quantile link for the binomial response,
into individual (model="quantile") and population
(model="pquantile")
Added new strategy
control.inla=list(strategy="adaptive") which use the
simplified.laplace approximations for fixed effects and
low-dimensional model components, and the gaussian
approximation
otherwise. The argument
adaptive.max in control.inla
determines what is low-dimensional in this
context (default 10).
Removed some code not used anymore
news(package="INLA"))ar1c
(Thanks to Virgilio Gomez Rubio)blas.num.threads in inla()R-3.5, both stable and testingpom (proportional odds model)R-3.4, both stable and testing.