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] }, { "page": "control.expert", "title": "control.expert", "concept": [ "control" ], "topics": [ "control.expert", "inla.set.control.expert.default" ] }, { "page": "control.family", "title": "control.family", "concept": [ "control" ], "topics": [ "control.family", "inla.set.control.family.default" ] }, { "page": "control.fixed", "title": "control.fixed", "concept": [ "control" ], "topics": [ "control.fixed", "inla.set.control.fixed.default" ] }, { "page": "control.gcpo", "title": "control.gcpo", "concept": [ "control" ], "topics": [ "control.gcpo", "inla.set.control.gcpo.default" ] }, { "page": "control.group", "title": "control.group", "concept": [ "control" ], "topics": [ "control.group", "inla.set.control.group.default" ] }, { "page": "control.hazard", "title": "control.hazard", "concept": [ "control" ], "topics": [ "control.hazard", "inla.set.control.hazard.default" ] }, { "page": "control.inla", "title": "control.inla", "concept": [ "control" ], "topics": [ "control.inla", "inla.set.control.inla.default" ] }, { "page": "control.lincomb", "title": "control.lincomb", "concept": [ "control" ], "topics": [ "control.lincomb", "inla.set.control.lincomb.default" ] }, { "page": "control.link", "title": "control.link", "concept": [ "control" ], "topics": [ "control.link", "inla.set.control.link.default" ] }, { "page": "control.lp.scale", "title": "control.lp.scale", "concept": [ "control" ], "topics": [ "control.lp.scale", "inla.set.control.lp.scale.default" ] }, { "page": "control.mix", "title": "control.mix", "concept": [ "control" ], "topics": [ "control.mix", "inla.set.control.mix.default" ] }, { "page": "control.mode", "title": "control.mode", "concept": [ "control" ], "topics": [ "control.mode", "inla.set.control.mode.default" ] }, { "page": "control.numa", "title": "control.numa", "concept": [ "control" ], "topics": [ "control.numa" ] }, { "page": "control.pom", "title": "control.pom", "concept": [ "control" ], "topics": [ "control.pom", "inla.set.control.pom.default" ] }, { "page": "control.predictor", "title": "control.predictor", "concept": [ "control" ], "topics": [ "control.predictor", "inla.set.control.predictor.default" ] }, { "page": "control.scopy", "title": "control.scopy", "concept": [ "control" ], "topics": [ "control.scopy", "inla.set.control.scopy.default" ] }, { "page": "control.sem", "title": "control.sem", "concept": [ "control" ], "topics": [ "control.sem", "inla.set.control.sem.default" ] }, { "page": "control.stiles", "title": "control.stiles", "concept": [ "control" ], "topics": [ "control.stiles", "inla.set.control.stiles.default" ] }, { "page": "control.taucs", "title": "control.taucs", "concept": [ "control" ], "topics": [ "control.taucs", "inla.set.control.taucs.default" ] }, { "page": "control.update", "title": "control.update", "concept": [ "control" ], "topics": [ "control.update", "inla.set.control.update.default" ] }, { "page": "control.vb", "title": "control.fixed", "concept": [ "control" ], "topics": [ "control.vb", "inla.set.control.vb.default" ] }, { "page": "crs_wkt", "title": "Handling CRS/WKT", "topics": [ "crs_wkt", "inla.crs_get_ellipsoid_radius", "inla.crs_get_lengthunit", "inla.crs_get_wkt", "inla.crs_is_geocent", "inla.crs_set_ellipsoid_radius", "inla.crs_set_lengthunit", "inla.wkt_get_ellipsoid_radius", "inla.wkt_get_lengthunit", "inla.wkt_is_geocent", "inla.wkt_set_ellipsoid_radius", "inla.wkt_set_lengthunit", "inla.wkt_unit_params" ] }, { "page": "cut", "title": "Group-wise model criticism using node-splitting", "topics": [ "cut", "inla.cut" ] }, { "page": "debug.graph", "title": "Debug a graph-file", "topics": [ "debug.graph", "inla.debug.graph" ] }, { "page": "Drivers", "title": "Time series with seasonal effect", "topics": [ "Drivers" ] }, { "page": "dryrun", "title": "Do a dryrun to extract some internal information upfront", "topics": [ "dryrun", "inla.dryrun" ] }, { "page": "Epil", "title": "Repeated measures on Poisson counts", "topics": [ "Epil" ] }, { "page": "extract.groups", "title": "Extract tagged boundary/internal segments.", "topics": [ "extract.groups", "extract.groups.inla.mesh.segment" ] }, { "page": "f", "title": "Define general Gaussian models in the INLA formula", "topics": [ "f" ] }, { "page": "fgn", "title": "Return the coefficients in the 3-component AR(1) mixture representing FGN(H)", "topics": [ "fgn", "inla.fgn" ] }, { "page": "Germany", "title": "Disease Mapping", "topics": [ "Germany" ] }, { "page": "graph.convert", "title": "INLA utility functions", "topics": [ "geobugs2inla", "graph.convert", "inla.geobugs2inla" ] }, { "page": "graph.matrix", "title": "Construct a neighbour-matrix from a 'graph'", "topics": [ "graph.matrix", "graph2matrix", "inla.graph2matrix", "inla.matrix2graph", "inla.spy", "spy" ] }, { "page": "idx", "title": "Convert indexes", "topics": [ "idx", "inla.idx" ] }, { "page": "inla", "title": "inla", "topics": [ "inla" ] }, { "page": "inla-class", "title": "inla estimation object class", "topics": [ "inla-class" ] }, { "page": "agaussian", "title": "Aggregate Gaussian into an equivalent observation", "topics": [ "agaussian", "aggregate.gaussian", "inla.agaussian" ] }, { "page": "ar", "title": "Convert between parameterizations for the AR(p) model", "topics": [ "ar.pacf2acf", "ar.pacf2phi", "ar.phi2acf", "ar.phi2pacf", "inla.ar.pacf2acf", "inla.ar.pacf2phi", "inla.ar.phi2acf", "inla.ar.phi2pacf", "pacf2acf", "pacf2phi", "phi2acf", "phi2pacf" ] }, { "page": "sm", "title": "Convert a matrix or sparse matrix into the sparse formate used by INLA", "topics": [ "inla.as.dgTMatrix", "inla.as.sparse" ] }, { "page": "wkt_tree", "title": "Internal WKT handling", "topics": [ "inla.as.wkt.wkt_tree", "inla.as.wkt_tree.wkt", "inla.wkt_tree_get_item", "inla.wkt_tree_set_item" ] }, { "page": "inla.barrier", "title": "Functions for defining the Barrier models", "topics": [ "barrier", "barrier.fem", "barrier.pcmatern", "barrier.polygon", "barrier.q", "inla.barrier", "inla.barrier.fem", "inla.barrier.pcmatern", "inla.barrier.polygon", "inla.barrier.q" ] }, { "page": "binary.install", "title": "Install alternative binary builds. (OBSOLETE: use 'inla.stiles.install()' instead)", "topics": [ "binary.install", "inla.binary.install" ] }, { "page": "inla.binary.path", "title": "Path of the inla binary in use", "topics": [ "inla.binary.path" ] }, { "page": "changelog", "title": "inla.changelog", "topics": [ "changelog", "inla.changelog", "inla.changes" ] }, { "page": "collect.results", "title": "Collect results from a inla-call", "topics": [ "collect.results", "inla.collect.results" ] }, { "page": "coxph", "title": "Convert a Cox proportional hazard model into Poisson regression", "topics": [ "cbind.data.frames", "coxph", "inla.coxph", "inla.rbind.data.frames" ] }, { "page": "cpo", "title": "Improved estimates for the CPO/PIT-values", "topics": [ "cpo.inla", "inla.cpo" ] }, { "page": "inla.CRS", "title": "Create a coordinate reference system object", "topics": [ "inla.CRS", "inla.wkt_predef" ] }, { "page": "CRSargs", "title": "Show expanded CRS arguments", "topics": [ "inla.as.CRS.list", "inla.as.CRSargs.list", "inla.as.list.CRS", "inla.as.list.CRSargs", "inla.CRSargs" ] }, { "page": "dev.new", "title": "Opens a new device", "topics": [ "inla.dev.new" ] }, { "page": "inla.diameter", "title": "Diameter of a point set", "topics": [ "inla.diameter", "inla.diameter.default", "inla.diameter.inla.mesh", "inla.diameter.inla.mesh.1d", "inla.diameter.inla.mesh.lattice", "inla.diameter.inla.mesh.segment" ] }, { "page": "doc", "title": "View documentation", "topics": [ "inla.doc", "inla.inla.doc" ] }, { "page": "external-package", "title": "Return the path to the cgeneric-library for a pre-compiled external package", "topics": [ "inla.external.lib" ] }, { "page": "inla.extract.el", "title": "Extract elements by matching name from container objects.", "topics": [ "inla.extract.el", "inla.extract.el.data.frame", "inla.extract.el.list", "inla.extract.el.matrix" ] }, { "page": "inla.fmesher.smorg", "title": "Compute various mesh related quantities.", "topics": [ "inla.fmesher.smorg" ] }, { "page": "inla.generate.colors", "title": "Generate text RGB color specifications.", "topics": [ "inla.generate.colors" ] }, { "page": "inlaEnv", "title": "Return the internal environment used by INLA", "topics": [ "get.inlaEnv", "inla.get.inlaEnv" ] }, { "page": "group", "title": "Group or cluster covariates", "topics": [ "inla.group" ] }, { "page": "group.cv", "title": "Compute group.cv-values", "topics": [ "inla.group.cv" ] }, { "page": "inla.has_PROJ6", "title": "PROJ6 detection", "topics": [ "inla.fallback_PROJ6", "inla.has_PROJ6", "inla.not_for_PROJ4", "inla.not_for_PROJ6", "inla.requires_PROJ6" ] }, { "page": "hyperpar", "title": "Improved estimates for the hyperparameters (classic-mode only)", "topics": [ "hyperpar.inla", "inla.hyperpar" ] }, { "page": "sampler", "title": "Produce samples from the approximated joint posterior for the hyperparameters", "topics": [ "hyperpar.sample", "hyperpar.sampler", "inla.hyperpar.sample", "inla.hyperpar.sampler" ] }, { "page": "inla.identical.CRS", "title": "Test CRS and inla.CRS for equality", "topics": [ "inla.identical.CRS" ] }, { "page": "iidkd", "title": "Provide samples from the 'iidkd' component (experimental)", "topics": [ "iidkd.sample", "inla.iidkd.sample" ] }, { "page": "knmodels", "title": "Spacetime interaction models", "topics": [ "inla.knmodels", "knmodels" ] }, { "page": "knmodels.sample", "title": "Spacetime interaction models sampler function", "topics": [ "inla.knmodels.sample" ] }, { "page": "residuals", "title": "Kolmogorov-Smirnov Test Plots", "topics": [ "inla.ks.plot", "ks.plot" ] }, { "page": "list-models", "title": "List available model components, likelihoods, priors, etc", "topics": [ "inla.list.models", "list.models" ] }, { "page": "inla.matern.cov", "title": "Numerical evaluation of Matern and related covariance functions.", "topics": [ "inla.matern.cov", "inla.matern.cov.s2" ] }, { "page": "mdata", "title": "Create an mdata-object for INLA", "topics": [ "as.inla.mdata", "inla.mdata", "is.inla.mdata", "mdata", "print.inla.mdata" ] }, { "page": "inla.mesh.1d", "title": "Function space definition objects for 1D SPDE models.", "topics": [ "inla.mesh.1d", "inla.mesh.1d.fem" ] }, { "page": "inla.mesh.1d.A", "title": "Mapping matrix for 1D meshes", "topics": [ "inla.mesh.1d.A", "inla.mesh.1d.bary" ] }, { "page": "inla.mesh.2d", "title": "High-quality triangulations", "topics": [ "inla.mesh.2d" ] }, { "page": "meshassessment", "title": "Interactive mesh building and diagnostics", "topics": [ "inla.mesh.assessment" ] }, { "page": "inla.mesh.basis", "title": "Basis functions for inla.mesh", "topics": [ "inla.mesh.basis" ] }, { "page": "inla.mesh.boundary", "title": "Constraint segment extraction for inla.mesh", "topics": [ "inla.mesh.boundary", "inla.mesh.interior" ] }, { "page": "inla.mesh.components", "title": "Compute connected mesh subsets", "topics": [ "inla.mesh.components" ] }, { "page": "inla.mesh.create", "title": "Low level function for high-quality triangulations", "topics": [ "inla.delaunay", "inla.mesh", "inla.mesh.create" ] }, { "page": "inla.mesh.deriv", "title": "Directional derivative matrices for functions on meshes.", "topics": [ "inla.mesh.deriv" ] }, { "page": "inla.mesh.fem", "title": "Finite element matrices", "topics": [ "inla.mesh.fem" ] }, { "page": "inla.mesh.lattice", "title": "Lattice grids for inla.mesh", "topics": [ "inla.mesh.lattice" ] }, { "page": "inla.mesh.map", "title": "Coordinate mappings for 'inla.mesh' projections.", "topics": [ "inla.mesh.map", "inla.mesh.map.lim" ] }, { "page": "inla.mesh.project", "title": "Methods for projecting to/from an inla.mesh", "topics": [ "inla.mesh.project", "inla.mesh.project.inla.mesh", "inla.mesh.project.inla.mesh.1d", "inla.mesh.project.inla.mesh.projector", "inla.mesh.projector", "inla.mesh.projector.inla.mesh", "inla.mesh.projector.inla.mesh.1d" ] }, { "page": "inla.mesh.query", "title": "High-quality triangulations", "topics": [ "inla.mesh.query" ] }, { "page": "inla.mesh.segment", "title": "Constraint segments for inla.mesh", "topics": [ "inla.contour.segment", "inla.mesh.segment" ] }, { "page": "models", "title": "Valid models in INLA", "topics": [ "inla.models" ] }, { "page": "nmix.lambda.fitted", "title": "Estimate posterior distributions of fitted lambda values", "topics": [ "inla.nmix.fitted", "inla.nmix.lambda.fitted", "nmix.lambda.fitted" ] }, { "page": "inla.nonconvex.hull", "title": "Nonconvex set extensions.", "topics": [ "inla.nonconvex.hull", "inla.nonconvex.hull.basic" ] }, { "page": "options", "title": "Set and get global options for INLA", "topics": [ "inla.getOption", "inla.option", "inla.options", "inla.setOption" ] }, { "page": "inla.over_sp_mesh", "title": "Check which mesh triangles are inside a polygon", "topics": [ "inla.over_sp_mesh" ] }, { "page": "inla.pin", "title": "Control main thread pinning for INLA (experimental)", "topics": [ "inla.pin", "inla.unpin" ] }, { "page": "priors.used", "title": "Print priors used", "topics": [ "inla.priors.used", "priors.used" ] }, { "page": "prune", "title": "Prune the INLA-package", "topics": [ "inla.prune", "prune" ] }, { "page": "reorderings", "title": "Reorderings methods for sparse matrices", "topics": [ "inla.reorderings", "reorderings" ] }, { "page": "rerun", "title": "Rerun an analysis", "topics": [ "inla.rerun", "rerun" ] }, { "page": "inla.run.many", "title": "inla.run.many", "topics": [ "inla.run.many" ] }, { "page": "posterior.sample", "title": "Generate samples, and functions thereof, from an approximated posterior of a fitted model", "topics": [ "inla.posterior.sample", "inla.posterior.sample.eval", "inla.sample", "posterior.sample", "posterior.sample.eval" ] }, { "page": "inla.simplify.curve", "title": "Recursive curve simplification.", "topics": [ "inla.simplify.curve" ] }, { "page": "inla.sp_get_crs", "title": "Extract CRS information", "topics": [ "inla.sp_get_crs" ] }, { "page": "inla.spde.make.A", "title": "Observation/prediction matrices for mesh models.", "topics": [ "inla.spde.make.A" ] }, { "page": "inla.spde.make.block.A", "title": "Observation matrices for mesh models.", "topics": [ "inla.spde.make.block.A" ] }, { "page": "inla.spde.make.index", "title": "SPDE model index vector generation", "topics": [ "inla.spde.make.index" ] }, { "page": "inla.spde.models", "title": "List SPDE models supported by inla.spde objects", "topics": [ "inla.spde.models", "inla.spde1.models", "inla.spde2.models" ] }, { "page": "inla.spde.precision", "title": "Precision matrices for SPDE models", "topics": [ "inla.spde.precision", "inla.spde.precision.inla.spde1", "inla.spde.precision.inla.spde2", "inla.spde1.precision", "inla.spde2.precision" ] }, { "page": "inla.spde.result", "title": "SPDE result extraction from INLA estimation results", "topics": [ "inla.spde.result", "inla.spde.result.inla.spde1", "inla.spde.result.inla.spde2", "inla.spde1.result", "inla.spde2.result" ] }, { "page": "inla.spde.sample", "title": "Sample from SPDE models", "topics": [ "inla.spde.sample", "inla.spde.sample.default", "inla.spde.sample.inla.spde" ] }, { "page": "inla.spde1.create", "title": "Old SPDE model objects for INLA", "topics": [ "inla.spde1", "inla.spde1.create", "inla.spde1.imatern", "inla.spde1.matern", "inla.spde1.matern.osc" ] }, { "page": "inla.spde2.generic", "title": "Generic spde2 model creation.", "topics": [ "inla.spde2", "inla.spde2.generic" ] }, { "page": "inla.spde2.matern", "title": "Matern SPDE model object for INLA", "topics": [ "inla.spde2.matern", "inla.spde2.theta2phi0", "inla.spde2.theta2phi1", "inla.spde2.theta2phi2" ] }, { "page": "inla.spde2.matern.sd.basis", "title": "Approximate variance-compensating basis functions", "topics": [ "inla.spde2.matern.sd.basis" ] }, { "page": "inla.spde2.pcmatern", "title": "Matern SPDE model object with PC prior for INLA", "topics": [ "inla.spde2.pcmatern" ] }, { "page": "inla.spTransform", "title": "Wrapper method for 'fmesher::fm_transform'", "topics": [ "inla.spTransform" ] }, { "page": "remote", "title": "Setup remote computing", "topics": [ "inla.remote", "inla.ssh.copy.id", "ssh.copy.id" ] }, { "page": "inla.stack", "title": "Data stacking for advanced INLA models", "topics": [ "inla.stack", "inla.stack.A", "inla.stack.compress", "inla.stack.data", "inla.stack.index", "inla.stack.join", "inla.stack.LHS", "inla.stack.remove.unused", "inla.stack.response", "inla.stack.RHS", "inla.stack.sum", "print.inla.data.stack" ] }, { "page": "inla.stiles.releases", "title": "Binary releases available to install", "topics": [ "inla.stiles.releases" ] }, { "page": "surv", "title": "Create a Survival Object for INLA", "topics": [ "as.inla.surv", "inla.surv", "is.inla.surv", "plot.inla.surv", "print.inla.surv" ] }, { "page": "inla.tempdir", "title": "inla.tempdir", "topics": [ "inla.tempdir" ] }, { "page": "upgrade", "title": "Upgrade the INLA-package", "topics": [ "inla.update", "inla.upgrade" ] }, { "page": "version", "title": "Show the version of the INLA-package", "topics": [ "inla.version", "version" ] }, { "page": "jmarginal", "title": "Sample, transform and evaluate from a joint marginal approximation", "topics": [ "1djmarginal", "inla.1djmarginal", "inla.joint.marginal", "inla.joint.marginal.eval", "inla.rjmarginal", "inla.rjmarginal.eval", "inla.tjmarginal", "joint.marginal", "joint.marginal.eval", "print.inla.jmarginal", "print.summary.inla.jmarginal", "rjmarginal", "rjmarginal.eval", "summary.inla.jmarginal", "tjmarginal" ] }, { "page": "jp", "title": "Joint-prior models", "topics": [ "inla.jp.define", "jp", "jp.define" ] }, { "page": "Kidney", "title": "Kidney infection data", "topics": [ "Kidney" ] }, { "page": "lattice2node", "title": "Functions to define mapping between a lattice and nodes", "topics": [ "inla.lattice2node", "inla.lattice2node.mapping", "inla.matrix2vector", "inla.node2lattice", "inla.node2lattice.mapping", "inla.vector2matrix", "lattice2node", "lattice2node.mapping", "matrix2vector", "node2lattice", "node2lattice.mapping", "vector2matrix" ] }, { "page": "Leuk", "title": "The Leukemia data", "topics": [ "Leuk", "Leukemia" ] }, { "page": "lines.inla.mesh.segment", "title": "Draw 'inla.mesh.segment' objects.", "topics": [ "lines.inla.mesh.segment" ] }, { "page": "link-functions", "title": "Link functions in INLA", "topics": [ "inla.link", "inla.link.cauchit", "inla.link.ccloglog", "inla.link.cgevit", "inla.link.cloglog", "inla.link.gevit", "inla.link.identity", "inla.link.invalid", "inla.link.invcauchit", "inla.link.invccloglog", "inla.link.invcgevit", "inla.link.invcloglog", "inla.link.inverse", "inla.link.invgevit", "inla.link.invidentity", "inla.link.invinvalid", "inla.link.invinverse", "inla.link.invlog", "inla.link.invlogit", "inla.link.invloglog", "inla.link.invneglog", "inla.link.invprobit", "inla.link.invqpoisson", "inla.link.invrobit", "inla.link.invsn", "inla.link.invtan", "inla.link.invtan.pi", "inla.link.log", "inla.link.logit", "inla.link.loglog", "inla.link.neglog", "inla.link.probit", "inla.link.robit", "inla.link.sn", "inla.link.tan", "inla.link.tan.pi", "link" ] }, { "page": "local_inla_options", "title": "Helper for locally setting inla options", "topics": [ "local_inla_options" ] }, { "page": "lincomb", "title": "Create linear combinations", "topics": [ "inla.make.lincomb", "inla.make.lincombs", "make.lincomb", "make.lincombs" ] }, { "page": "marginal", "title": "Functions which operates on marginals", "topics": [ "dmarginal", "emarginal", "hpdmarginal", "inla.dmarginal", "inla.emarginal", "inla.hpdmarginal", "inla.is.marginal", "inla.marginal", "inla.mmarginal", "inla.pmarginal", "inla.qmarginal", "inla.rmarginal", "inla.smarginal", "inla.tmarginal", "inla.zmarginal", "marginal", "mmarginal", "pmarginal", "qmarginal", "rmarginal", "smarginal", "zmarginal" ] }, { "page": "merge", "title": "Merge a mixture of 'inla'-objects", "topics": [ "inla.merge", "merge.inla" ] }, { "page": "meshbuilder", "title": "Interactive mesh building and diagnostics", "topics": [ "meshbuilder" ] }, { "page": "Munich", "title": "The Munich rent data", "topics": [ "Munich" ] }, { "page": "nwEngland", "title": "The North West England map", "topics": [ "nwEngland" ] }, { "page": "Oral", "title": "~~ data name/kind ... ~~", "topics": [ "Oral" ] }, { "page": "param2.matern.orig", "title": "Parameter settings for 'inla.spde2.matern' models.", "topics": [ "param2.matern.orig" ] }, { "page": "pc-alphaw", "title": "Utility functions for the PC prior for the 'alpha' parameter in the Weibull likelihood", "topics": [ "inla.pc.alphaw", "inla.pc.dalphaw", "inla.pc.palphaw", "inla.pc.qalphaw", "inla.pc.ralphaw", "pc.alphaw", "pc.dalphaw", "pc.palphaw", "pc.qalphaw", "pc.ralphaw" ] }, { "page": "pc-ar", "title": "Utility functions for the PC prior for a an AR(p) model", "topics": [ "ar.dpacf", "ar.rpacf", "inla.pc.ar", "inla.pc.ar.dpacf", "inla.pc.ar.rpacf", "pc.ar" ] }, { "page": "pc-cor0", "title": "Utility functions for the PC prior for correlation in AR(1)", "topics": [ "inla.pc.cor0", "inla.pc.dcor0", "inla.pc.pcor0", "inla.pc.qcor0", "inla.pc.rcor0", "pc.cor0", "pc.dcor0", "pc.pcor0", "pc.qcor0", "pc.rcor0" ] }, { "page": "pc-cor1", "title": "Utility functions for the PC prior for correlation in AR(1)", "topics": [ "inla.pc.cor1", "inla.pc.dcor1", "inla.pc.pcor1", "inla.pc.qcor1", "inla.pc.rcor1", "pc.cor1", "pc.dcor1", "pc.pcor1", "pc.qcor1", "pc.rcor1" ] }, { "page": "pc-cormat", "title": "Utility functions for the PC prior for a correlation matrix", "topics": [ "cormat.dim2p", "cormat.dtheta", "cormat.p2dim", "cormat.permute", "cormat.R2r", "cormat.r2R", "cormat.R2theta", "cormat.r2theta", "cormat.rtheta", "cormat.theta2R", "cormat.theta2r", "inla.pc.cormat", "inla.pc.cormat.dim2p", "inla.pc.cormat.dtheta", "inla.pc.cormat.p2dim", "inla.pc.cormat.permute", "inla.pc.cormat.R2r", "inla.pc.cormat.r2R", "inla.pc.cormat.R2theta", "inla.pc.cormat.r2theta", "inla.pc.cormat.rtheta", "inla.pc.cormat.theta2R", "inla.pc.cormat.theta2r", "pc.cormat" ] }, { "page": "pc-t", "title": "PC-prior for dof in a standardized Student-t", "topics": [ "inla.pc.ddof", "inla.pc.dof", "inla.pc.t", "pc.ddof", "pc.dof", "pc.t" ] }, { "page": "pc-gamma", "title": "Utility functions for the PC prior for 'Gamma(1/a, 1/a)'", "topics": [ "inla.pc.dgamma", "inla.pc.gamma", "inla.pc.pgamma", "inla.pc.qgamma", "inla.pc.rgamma", "pc.dgamma", "pc.gamma", "pc.pgamma", "pc.qgamma", "pc.rgamma" ] }, { "page": "pc-gammacount", "title": "Utility functions for the PC prior for the 'gammacount' likelihood", "topics": [ "inla.pc.dgammacount", "inla.pc.gammacount", "inla.pc.pgammacount", "inla.pc.qgammacount", "inla.pc.rgammacount", "pc.dgammacount", "pc.gammacount", "pc.pgammacount", "pc.qgammacount", "pc.rgammacount" ] }, { "page": "pc-gev", "title": "Utility functions for the PC prior for the 'tail' parameter in the GEV likelihood", "topics": [ "inla.pc.dgevtail", "inla.pc.gevtail", "inla.pc.pgevtail", "inla.pc.qgevtail", "inla.pc.rgevtail", "pc.dgevtail", "pc.gevtail", "pc.pgevtail", "pc.qgevtail", "pc.rgevtail" ] }, { "page": "pc-multvar", "title": "Multivariate PC priors", "topics": [ "inla.pc.multvar", "inla.pc.multvar.h.default", "inla.pc.multvar.simplex", "inla.pc.multvar.simplex.d", "inla.pc.multvar.simplex.r", "inla.pc.multvar.sphere", "inla.pc.multvar.sphere.d", "inla.pc.multvar.sphere.r", "pc.multvar", "pc.multvar.h.default", "pc.multvar.simplex", "pc.multvar.simplex.d", "pc.multvar.simplex.r", "pc.multvar.sphere", "pc.multvar.sphere.d", "pc.multvar.sphere.r" ] }, { "page": "pc-prec", "title": "Utility functions for the PC prior for the precision", "topics": [ "inla.pc.dprec", "inla.pc.pprec", "inla.pc.prec", "inla.pc.qprec", "inla.pc.rprec", "pc.dprec", "pc.pprec", "pc.prec", "pc.qprec", "pc.rprec" ] }, { "page": "prw2.range", "title": "Utility functions for the PC prior for range in PRW2", "topics": [ "inla.pc.prw2.drange", "inla.pc.prw2.prange", "inla.pc.prw2.qrange", "inla.pc.prw2.rrange", "pc.prw2.range", "prw2.d" ] }, { "page": "pc-sn", "title": "Utility functions for the PC prior for 'skewness' in the skew-normal linkfunction and likelihood", "topics": [ "inla.pc.dsn", "inla.pc.psn", "inla.pc.qsn", "inla.pc.rsn", "inla.pc.sn", "pc.dsn", "pc.psn", "pc.qsn", "pc.rsn", "pc.sn" ] }, { "page": "pc-vm0", "title": "Utility functions for the PC prior for the precision", "topics": [ "inla.pc.dvm0", "inla.pc.pvm0", "inla.pc.qvm0", "inla.pc.rvm0", "inla.pc.vm0", "pc.dvm0", "pc.pvm0", "pc.qvm0", "pc.rvm0", "pc.vm0" ] }, { "page": "pc-vminf", "title": "Utility functions for the PC prior for the concentration of von Mises distribution with point mass base model", "topics": [ "inla.pc.dvminf", "inla.pc.pvminf", "inla.pc.qvminf", "inla.pc.rvminf", "inla.pc.vminf", "pc.dvminf", "pc.pvminf", "pc.qvminf", "pc.rvminf", "pc.vminf" ] }, { "page": "plot", "title": "Default INLA plotting", "topics": [ "inla.plot", "plot.inla" ] }, { "page": "plot.inla.mesh", "title": "Draw a triangulation mesh object", "topics": [ "plot.inla.mesh" ] }, { "page": "plot.inla.trimesh", "title": "Low level triangulation mesh plotting", "topics": [ "plot.inla.trimesh" ] }, { "page": "PRborder", "title": "The PRborder data", "topics": [ "PRborder" ] }, { "page": "print", "title": "Print an INLA fit", "topics": [ "print.inla" ] }, { "page": "PRprec", "title": "The PRprec data", "topics": [ "PRprec" ] }, { "page": "qinv", "title": "Computes (parts of) the inverse of a SPD sparse matrix", "topics": [ "inla.qinv", "qinv" ] }, { "page": "qreordering", "title": "Compute the reordering using the GMRFLib implementation", "topics": [ "inla.qreordering", "qreordering" ] }, { "page": "qsample", "title": "Generate samples from a GMRF using the GMRFLib implementation", "topics": [ "inla.qsample", "qsample" ] }, { "page": "qsolve", "title": "Solves linear SPD systems", "topics": [ "inla.qsolve", "qsolve" ] }, { "page": "read.graph", "title": "Read and write a graph-object", "topics": [ "inla.graph", "inla.read.graph", "inla.write.graph", "plot.inla.graph", "print.inla.graph.summary", "read.graph", "summary.inla.graph", "write.graph" ] }, { "page": "rgeneric", "title": "rgeneric models", "topics": [ "inla.rgeneric.ar1.model", "inla.rgeneric.ar1.model.opt", "inla.rgeneric.define", "inla.rgeneric.iid.model", "inla.rgeneric.q", "inla.rgeneric.wrapper", "rgeneric", "rgeneric.ar1.model", "rgeneric.define", "rgeneric.iid.model", "rgeneric.q", "rgeneric.wrapper" ] }, { "page": "rprior.define", "title": "Define prior in R", "topics": [ "inla.rprior.define", "rprior", "rprior.define" ] }, { "page": "Salm", "title": "Extra-Poisson variation in dose-response study", "topics": [ "Salm" ] }, { "page": "scale.model", "title": "Scale an intrinsic GMRF model", "topics": [ "inla.scale.model", "inla.scale.model.internal", "scale.model" ] }, { "page": "scopy.define", "title": "Get the parameterisation of the 'scopy' model", "topics": [ "inla.scopy.define", "scopy.define" ] }, { "page": "scopy.summary", "title": "Computes the mean and stdev for the spline from 'scopy'", "topics": [ "inla.scopy.summary", "scopy.summary" ] }, { "page": "Scotland", "title": "Conditional Autoregressive (CAR) model for disease mapping", "topics": [ "Scotland" ] }, { "page": "Seeds", "title": "Factorial design", "topics": [ "Seeds" ] }, { "page": "SPDEtoy", "title": "toy simulated data set for the SPDE tutorial", "topics": [ "SPDEtoy" ] }, { "page": "stiles.install", "title": "Install a pre-built INLA binary with sTiles support", "topics": [ "inla.stiles.install", "inla.stiles.status", "stiles.install" ] }, { "page": "stiles.utils", "title": "sTiles utils: streaming spy plots and graph<->mtx I/O", "topics": [ "inla.stiles.graph2mtx", "inla.stiles.mtx2graph", "inla.stiles.spy.graph", "inla.stiles.spy.mtx", "stiles.utils" ] }, { "page": "summary", "title": "Summary for a INLA fit", "topics": [ "print.summary.inla", "summary.inla", "summary.surv.inla" ] }, { "page": "summary.inla.mesh", "title": "Summarizing triangular mesh objects", "topics": [ "print.summary.inla.mesh", "summary.inla.mesh" ] }, { "page": "Surg", "title": "Surgical: Institutional ranking", "topics": [ "Surg" ] }, { "page": "SurvSim", "title": "Survival data", "topics": [ "SurvSim" ] }, { "page": "Tokyo", "title": "Binomial time series", "topics": [ "Tokyo" ] }, { "page": "Zambia", "title": "Semiparametric regression", "topics": [ "Zambia" ] } ], "_readme": "https://github.com/hrue/r-inla/raw/HEAD/README.md", "_rundeps": [ "class", "classInt", "cli", "DBI", "dplyr", "e1071", "fmesher", "generics", "glue", "KernSmooth", "lattice", "lifecycle", "magrittr", "Matrix", "MatrixModels", "pillar", "pkgconfig", "proxy", "R6", "Rcpp", "rlang", "s2", "sf", "sp", "splancs", "tibble", "tidyselect", "units", "utf8", "vctrs", "withr", "wk" ], "_vignettes": [ { "source": "a-note-about-values.Rmd", "filename": "a-note-about-values.pdf", "title": "A note about values", "author": "Håvard Rue (hrue@r-inla.org) & Sigrunn Holbek Sørbye (sigrunn.sorbye@uit.no)", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "An example", "Another example" ], "created": "2025-12-01 13:09:25", "modified": "2025-12-06 14:56:13", "commits": 2 }, { "source": "jmarginal.Rmd", "filename": "jmarginal.pdf", "title": "Approximating joint marginals", "author": "Cristian Chiuchiolo and Haavard Rue", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Theory reference", "First example", "Deterministic Joint approximation", "References" ], "created": "2020-07-21 19:15:28", "modified": "2023-06-22 09:03:09", "commits": 12 }, { "source": "stack-with-factors.Rmd", "filename": "stack-with-factors.pdf", "title": "Avoiding trouble with factors in inla.stack", "author": "Elias T. Krainski (elias@r-inla.org)", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Working with factors in R", "Dealing with factors in inla.stack()", "When there is a prediction scenario", "References" ], "created": "2018-02-04 09:10:04", "modified": "2023-04-02 21:32:55", "commits": 8 }, { "source": "bGEVtutorial1-2.Rmd", "filename": "bGEVtutorial1-2.pdf", "title": "Blended GEV: a tutorial using R-INLA", "author": "\\normalfont{Daniela Castro-Camilo {\\small{$\\bullet$}} daniela.castrocamilo@glasgow.ac.uk}", "engine": "knitr::rmarkdown", "headings": [ "A reparametrisation of the GEV", "The blended GEV model", "Simulated example 1", "Data simulation", "Prior specification", "Control variables", "INLA fit", "Simulated example 2", "Data simulation", "Prior specification", "INLA fit", "Simulated example 3", "Data simulation", "INLA fit", "Notes", "Linear predictor for the bGEV model", "PC prior for the tail parameter", "About $\\texttt", "Tools" ], "created": "2020-06-29 18:52:58", "modified": "2024-01-24 08:47:11", "commits": 19 }, { "source": "conditional_logit.Rmd", "filename": "conditional_logit.pdf", "title": "Conditional Logistic Regression Model", "author": "Stefanie Muff (stefanie.muff@uzh.ch), Johannes Signer, John Fieberg", "engine": "knitr::rmarkdown", "headings": [ "Parametrization", "Hyperparameters", "Specification", "Example", "References" ], "created": "2018-08-08 22:17:30", "modified": "2022-04-25 07:33:31", "commits": 8 }, { "source": "conditional-sampling.Rmd", "filename": "conditional-sampling.pdf", "title": "Conditional sampling from a fitted model", "author": "Haavard Rue (hrue@r-inla.org)", "engine": "knitr::rmarkdown", "headings": [], "created": "2018-02-04 09:10:04", "modified": "2022-11-21 19:09:18", "commits": 9 }, { "source": "AA-group-cv.Rmd", "filename": "AA-group-cv.pdf", "title": "Cross-validation and group-cross-validation in INLA", "author": "Zhedong Liu (zhedong.liu@kaust.edu.sa)", "engine": "knitr::rmarkdown", "headings": [ "References" ], "created": "2023-04-02 21:06:36", "modified": "2025-10-13 17:11:48", "commits": 4 }, { "source": "rgeneric.Rmd", "filename": "rgeneric.pdf", "title": "Defining a latent model in R or C", "author": "Haavard Rue (hrue@r-inla.org)", "engine": "knitr::rmarkdown", "headings": [], "created": "2018-02-04 09:10:04", "modified": "2024-05-26 17:52:52", "commits": 28 }, { "source": "Dirichlet-CoDa.Rmd", "filename": "Dirichlet-CoDa.pdf", "title": "Fitting CoDa using the Logistic Gaussian distribution with Dirichlet covariance structure", "author": "\\normalfont{Joaquín Martínez-Minaya {\\small{$\\bullet$}} jmarmin@eio.upv.es}", "engine": "knitr::rmarkdown", "headings": [ "An introduction to the Logistic Normal Dirichlet Regression", "Simulated example I (Type II)", "Data simulation", "Defining hyperparameters and dimensionality of the response", "Simulating a covariate", "alr-coordinates", "Data in the simplex", "Plotting the simulated data", "Data preparation for fitting", "Index for individual", "Extending the dataset", "Response in R-INLA", "Covariates in R-INLA", "inla.stack", "Fitting the model", "Fit in R-INLA", "Marginal posterior distribution of the fixed effects", "Marginal Posterior distribution of the hyperparameters", "Predicting for a new observation", "Preparing dataset for predictions", "Preparing inla.stack for predictions", "Prediction", "Extracting predictions using inla.posterior.sample", "Predictions in the simplex", "References" ], "created": "2023-08-25 15:22:01", "modified": "2024-03-19 09:53:03", "commits": 3 }, { "source": "Tutorial_barrier_global.Rmd", "filename": "Tutorial_barrier_global.pdf", "title": "Global oceanic barrier model on the sphere", "author": "Alba Fuster-Alonso^[afuster@icm.csic.es, Institut de Ciències del Mar (ICM) - CSIC, Barcelona, Spain.] $;$ Elias T Krainski^[King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.] $;$ Haavard Rue^[King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia.] $;$ Finn Lindgren^[University of Edinburgh (UoE), Edinburgh, Scotland.]", "engine": "knitr::rmarkdown", "headings": [ "Introduction" ], "created": "2024-02-21 07:35:35", "modified": "2025-11-27 05:47:15", "commits": 4 }, { "source": "Apptainer.Rmd", "filename": "Apptainer.pdf", "title": "Installation of INLA and inlabru with Apptainer on HPC", "author": "Man Ho Suen (m.h.suen@sms.ed.ac.uk)", "engine": "knitr::rmarkdown", "headings": [ "Installation Procedures" ], "created": "2022-10-25 07:10:13", "modified": "2023-04-02 21:32:55", "commits": 2 }, { "source": "multinomial.Rmd", "filename": "multinomial.pdf", "title": "Multinomial logit models with INLA", "author": "Francesco Serafini (serafini314@gmail.com)", "engine": "knitr::rmarkdown", "headings": [ "Abstract", "Theoretical part", "On the Multinomial logit model", "On the Poisson Trick", "Practical Part", "On the Multinomial Data and Model Parameters", "Data structure", "A Simple Model", "Changing the size", "A First Random Effect", "Time Random Effects", "Discrete Spatial Random effect", "Continuos spatial random effect", "Yogurt Data", "Model", "Conclusion", "References" ], "created": "2018-11-04 06:53:34", "modified": "2024-04-25 16:36:03", "commits": 15 }, { "source": "scale-model.Rmd", "filename": "scale-model.pdf", "title": "Scaling IGMRF-models in R-INLA", "author": "Sigrunn Holbek S\\o rbye", "engine": "knitr::rmarkdown", "headings": [], "created": "2023-04-10 23:07:03", "modified": "2023-04-17 13:25:03", "commits": 2 }, { "source": "old-faq.Rmd", "filename": "old-faq.pdf", "title": "Short tutorials from old www-page", "author": "Haavard Rue (hrue@r-inla.org)", "engine": "knitr::rmarkdown", "headings": [ "Contents", "Introduction", "User-defined priors for the hyperparameters", "Does INLA support the use of different link-functions?", "How can I do predictions using INLA?", "Some of the models needs a graph, how do I specify it?", "How \\texttt", "Can INLA deal with missing covariates?", "Compute cross-validation or predictive measures of fit", "I have access to a remote Linux/MacOS server, is it possible to run the computations remotely and running R locally?", "Posteriors for linear combinations", "INLA seems to work great for near all cases, but are there cases where INLA is known to have problems?", "Can I have the linear predictor from one model as a covariate in a different model?", "Latent models, likelihoods and priors.", "Copying a model", "Replicate a model", "Models with more than one type of likelihood", "Models where the response/data depends on linear combinations of the \"linear predictor\" (or the sum of \"fixed\" and \"random\" effects)" ], "created": "2020-08-07 10:47:30", "modified": "2024-12-04 18:42:20", "commits": 18 }, { "source": "svc.Rmd", "filename": "svc.pdf", "title": "Spatially Varying Coefficient Models with R-INLA", "author": "Timothy D. Meehan (tmeeha@gmail.com), Elias T. Krainski, Finn Lindgren, and Håvard Rue", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Model", "Environment", "Import data", "Make spatial data", "SPDE components", "Modeling mesh", "SPDE model object", "Index sets", "Projector matrices", "Data stack for model fitting", "Model formula", "Run model", "Model summaries", "SVC maps", "More information", "Citations" ], "created": "2022-08-10 08:50:17", "modified": "2026-04-20 07:05:48", "commits": 14 }, { "source": "SPDE2mdatasurv.Rmd", "filename": "SPDE2mdatasurv.pdf", "title": "SPDE example with multiple kind of outcomes", "author": "Elias T Krainski", "engine": "knitr::rmarkdown", "headings": [ "Abstract", "Introduction", "The spatial domain", "A spatial field", "Spatial sub-domains", "Covariates", "Outcomes", "First outcome: aggregated Gaussian", "Second outcome: Survival", "Third outcome: Count under exposure", "Data model setup", "SPDE model setup", "Linear predictor components", "Building data stacks", "Fitting the 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