Changes in version 2.0.11 - New ranef S3 generic and ranef.glmmVA method: extracts random-effect estimates from a glmmVA object. Bugfixes - Fixed glmmVA ignoring 0+/-1 intercept suppression in the formula (issue #250). - Fixed diag(a+b|grp) (issue #241). - Fixed incorrect trmsize[1,] computation in row.eff formula processing. Changes in version 2.0.10 (2026-05-10) - CRAN update version 2.0.10 - See updates in 2.0.6-2.0.10 Changes in version 2.0.9 - Added beta-binomial family with method = "LA" - Method is not automatically changed if family is not implemented. Instead informative message is printed about available options. - Added an option to choose which response variables residual diagnostics are plotted. Bugfixes - Residual Correlation calculation didn't take into account adjustments for 01-model. Fixed. Changes in version 2.0.8 - New predictSR function for predicting species richness - New poisson-binomial PMF function (for predictSR) - New residuals.predict.SR function for dunn-smyth residuals of species richness - New predictPairwise function (simple wrapper for predicting joint occurrence) - Implemented prediction functionality with when providing new measurements for covariates in the row effects - Improved output of AICc.gllvm to be in line with the AIC and BIC returned tables - AUC added to goodnessOfFit statistics - Added VA-EVA hybrid approximation for the orderedBeta model with logit link - Added 'spp' argument to predict.gllvm, for when only predictions are needed for selected species Bugfixes - row.eff was ignoring 'diag' - 2.0.7 did not install on ubuntu due to string error in new enum check - bugfix in plot.gllvm that left plots empty under particular settings - bugfix in nested random row effects - bugfix in phyloplot.gllvm that prevented uncertain random effects from being crossed out Changes in version 2.0.7 - Mixed response type model implemented - Added simulated confidence intervals to predict.gllvm, see #24 Changes in version 2.0.6 - Added cloglog link for binomial, ZIB and ZNIB. - Added negative binomial (1) (VA via PIG augmentation) - Ntrials can vary per site/species - New function to fit univariate GLMMs: glmmVA - New propto structure for random (row) effects (possibly with correlations) - lvCor compatible with num.lv.c - More generally expanded the (row.eff) formula interface for glmmVA to kronecker structures (e.g., corExp(0+a+b|group) has a 2x2 covarariance for the LHS and a nxn for the RHS) - Added Nagelkerke's, McFadden's and Cox & Snell's Pseudo r2 measures in goodnessOfFit - In predict.gllvm type = "class" implemented for ordinal and binomial models. - corWithin fixed to work also for not balanced study designs Bugfixes - Bugfix in VP for random effects in formula - Bugfix in starting values for models involving both random row effects and random species effects - Bugfix in predict for fourth-corner model with random effects species via lme4-style formula - Bugfix in prediction with random and fixed row effects - Bugfix goodnessOfFit fixed for ordinal model Changes in version 2.0.5 (2025-07-13) - For CRAN release 2.0.5 see updates for versions 2.0.3 - 2.0.5 - num.RR and num.lv with lvCor can now be combined - lvCor can be used with multiple (iid) terms - New start.optimizer and start.optim.method arguments for changing the optimizers for generating starting values, related to #229. - cex.spp in ordiplot.gllvm can now be a vector - Added zero-inflated binomial distribution - Added zero-n-inflated binomial distribution Bugfixes - Bug fixed in VP for mixed effects formula - Bug fixed for num.lv.c = 1 models - Bug fixed that crashed ordinal models with num.lv>0 and species-specific random effects - Bug fixed in residuals for ZIP and ZINB models Changes in version 2.0.4 - Logit and cumulative logit models with method = "VA" Changes in version 2.0.3 - Add option for scaling in getEnvironCor - Added logistic GLLVM with VA via polya-gamma augmentation (see Polson et al. 2012) - Added residual variance term in getResidualCov.gllvm for ordinal models - Boundary check for cumulative probit model - New 'ind.spp' argument for coefplot and RandomCoefPlot to possibly plot for fewer species - Implemented predict for species-specific random effects - Improved handling of provided 'start.fit' Bugfixes - Fixed a bug that caused phyloplot.gllvm to fail with trait models - Ensured that update.gllvm also adopts non-formula arguments - Default optimizer for random canonical coefficients was not set right for Tweedie - Bugfix for showing categorical ordination effects as centroids - Bugfix for getPredictErr and trait model - Bugfix for phylogenetic model with traits; the phylogenetic matrix was not passed on to the output - Bugfix for predict with constrained ordination and randomB - Fixed a rare bug that caused a warning message in starting value generation with square response matrices - Bugfix for starting values of family = "ordinal" and zeta.struc = "species" - Bug fixed for partial constrained/concurrent ordination with more than one conditioning variable Changes in version 2.0.2 (2025-04-08) Bugfixes - Fixed a bug that caused model failure when starting values for row effects could not be calculated - Fixed a bug that caused issues when using 'randomCoefPlot' in combination with lme4-type formula for the 4th corner model - Fixed a bug in the prediction error calculation of the 4th corner model fitted with method = "LA" - Fixed a bug in the starting values random reduced rank models when the design matrix is of reduced rank - Fixed a bug that occurred with 'starting.values = "zero"' for random reduced rank models with correlation parameters - Fixed a bug in the calculation of starting values for concurrent ordination with ordinal species responses and common cut-off parameters - Fixed a bug that caused the variance parameter of a second row effect to be fixed to the variance of the first - Fixed a bug that increased the duration for calculating starting values of some Tweedie models significantly Changes in version 2.0.1 (2025-04-01) - Added VA implementation of Tweedie - Added "band matrix" as a sparsity pattern for phylogenetic models, as alternative to the NNGP - Added 'tick.length' argument for phyplot.gllvm to control the tick length in the species-specific random effects plot - Improvement for the starting values of concurrent ordination - Added correlation canonical coefficients option for randomB="LV" - Added additional (LV-specific) variance parameters for randomB="P" - Default for rel.tol changed to 1e-10 - Default for NN changed to 10 - A Matern smoothness parameter changed to fixed value given by user by default Bug Fixes - Fixed a bug in the calculation of standard errors for models involving traits and a ZIP/ZINB response distribution. See #204. - Fixed a bug that prevented from incorporating correlated random effects via "formula" - Fixed a bug that prevented successfully incorporating phylogenetic random effects with traits - Fixed a bug in the confidence level of phyloplot.gllvm - Fixed a bug in residuals.gllvm - Fixed a bug in starting value generation - Fixed a bug in the number of parameters by logLik.gllvm for 'randomB' models with correlation parameters - Fixed a bug in the normalization constant for randomB="LV" - Fixed a bug in the variance partitioning for models with species random effects - Fixed a bug in extracting fourth corner coefficients, see #214 and #215 - Fixed a bug in standard errors involving row.eff = "random" - Fixed a bug that prevented using getEnvironCov with the fourth corner model - Fixed a bug in gllvm:::RRse - Fixed a bug which occurred when correlated latent variables are included and Variational covariance was anything else that diagonal Changes in version 2.0 (2024-11-26) - For CRAN release 2.0 see updates for versions 1.4.4 - 1.4.9 Changes in version 1.4.9 - Row.eff can now be used for community-level (species-common) effect - Both fixed and random at the same time (i.e., a mixed effects formula) - Does not allow for a single random intercept - Does not yet allow for between random effect correlation - New formula interface for phylogenetic model adapted to trait model too - New phyplot.gllvm function for plotting the phylogenetic random effects - Minor adjustment in the behavior of 'caption' in plot.gllvm Changes in version 1.4.8 - Added functionality for correlated random canonical coefficients - Changed "site.index" argument in getResidualCov.gllvm to "x", in line with getEnvironCov.gllvm - New vignette for the correlation structures of random effects and latent variables. Bug Fixes - Bug fixed for calculating residual covariances of quadratic concurrent ordination Changes in version 1.4.7 - Added "fungi" dataset by Abrego et al. 2022 - Added "kelpforest" dataset by Reed and Miller 2023 - New vignette for phylogenetic random effects - New vignette for percent cover data analysis - Function for calculating and plotting variance partitioning (varPartitioning.gllvm and plotVP) Changes in version 1.4.6 - Added a 'getLoadings' function for retrieving species' loadings - Added 'fac.center' argument in ordiplot to plot canonical coefficients of binary variables as points - Added a simple plotting function for the gllvm summary - Improved scaling for ordiplot with quadratic model and with biplot = FALSE - optima.gllvm and tolerances.gllvm for num.lv now correctly provide tolerances w.r.t. the scaled LV - Improved starting values for models with 'randomB' - 'which.Xcoef' in coefplot.gllvm now also works for fourth-corner models - Added intercept if beta0com=TRUE to coefplot.gllvm for fourth-corner models Bug Fixes - Bug fixed that prevented increasing he point size of sites in ordiplot with symbols = TRUE - Bug fixed in optima.gllvm for models with a single LV Changes in version 1.4.5 - Separated "n.init" functionality into gllvm.iter.R - Prep for parallelisation - Enabled parallelisation (see TMB::openmp) - Largely vectorized "residuals.gllvm", and residuals in "gllvm.aux" - Added covariance of random effects to summary - In preparation of emmeans support: moved the design matrix in "lv.X" to "lv.X.design". "lv.X" now stores the original supplied data.frame Bug Fixes - Bug in ZINB fixed Changes in version 1.4.4 - Removed "dependent.row" feature - Added possibility for multiple random row intercepts - Added possibility for (correlated) random species random effects - Can be plotted with "randomCoefPlot" - Added possibility to Phylogenetically structure the random species effects - Phylogenetic signal parameter is included as object$params$rho.sp - Can be covariate specific - num.RR and num.lv.c can now be larger than the number of predictors if randomB!=FALSE - Added "iid" option for "randomB" - Added a "getEnvironCov" function to extract species associations due to random covariate effects Changes in version 1.4.3 (2023-09-18) - For CRAN release 1.4.3 see updates for versions 1.4.2 and 1.4.3 Bug Fixes - Bug in correlated row effects fixed - Bug in getPredictErr for models fitted with LA fixed, and it returns now prediction errors for random slopes of X covariates as well - Bug in randomCoefplot fixed Changes in version 1.4.2 New Features - Added a correction factor to the second partial derivatives of the canonical coefficients for concurrent and constrained ordination - Added randomCoefPlot functionality of constrained and concurrent ordination models with random slopes. Currently not supported for models with quadratic responses - Summary now provides the possibility to calculate wald statistics across LVs or predictors for concurrent and constrained ordination - coef now renames parameter estimates with more intuitive names and allows to subset the parameter list with names - Tweedie power parameter is estimated now if set to NULL in `gllvm. - VA support for Zero-inflated poisson distribution - Zero-inflated negative-binomial distribution added - Binomial (Ntrials>1) support added (previously only Bernoulli) - Now allowed to have (some) NAs in the response data Bug Fixes - Fixed an issue with structured row-effects in concurrent and constrained ordination - Fixed a bug that prevented plotting prediction regions for constrained ordination with structured row-effects - No standard errors should be returned by optima.gllvm and tolerances.gllvm with randomB != FALSE - Species names were in the original order with order = TRUE in RandomCoefPlot - Fixed an issue that arose when {0,1} bounded parameters reached the bounds - Various bug fixes for constrained/concurrent ordination with random intercepts and random slopes - Bug in predictions with structured row intercepts was fixed, see issue #86 Changes in version 1.4.1 (2023-01-07) New Features - Computational stability of random slopes for constr. and concr. ordination significantly improved - Computational stability of quadratic model significantly improved - Unstructured VA covariance matrix for quadratic models with random intercepts - Added example for se.gllvm Bug Fixes - Bugfix in random slopes for concr. ordination with LV-specific variances and random row intercepts - Bugfix for quadratic model with Poisson, NB, gamma, or exponential responses - Bugfix in starting values for constrained and concurrent quadratic model Bug Fixes - Valgrind error fixed Changes in version 1.4.0 (2022-12-17) New Features - For CRAN release 1.4.0's new features see features described for versions 1.3.2-1.3.3 Bug Fixes - For bug fixes to CRAN release 1.4.0 see versions 1.3.2-1.3.3 Changes in version 1.3.3 New Features - The n.init option has been improved, so that it stops if no improved fit has been found after n.init.max (defaults to 10) iterations. - Row names from the data now carry over to the site scores, so that they can be displayed in ordiplot Bug Fixes - Memory allocation problem in development version fixed - Diagonal elements of loading matrix 'theta' fixed for fourth corner model - Bug in 'predict' for random slopes fixed, occurred when new x-covariate values were given Changes in version 1.3.2 New Features - Ordination with predictors (num.RR,num.lv.c) is now implemented with constrained optimization routines (alabama,nloptr) as long as the canonical coefficients are treated as fixed-effects. This follows from the necessary identifiability constraints. - The reduced-rank approximated predictor slopes of a multivariate regression can now be plotted (with confidence intervals) using coefplot. Not available yet for quadratic effects. - Separate checks are put in place to warn users if the constraints on the canonical coefficients (orthogonality of the columns) have not converged. - Separate checks are put in place to warn users if the coefficients of a quadratic model have not converged - Canonical coefficients in ordination with predictors (num.RR,num.lv.c) can now be treated as random-effects using the 'randomB' argument. For the moment, all need to be either random or fixed, no mixing. Prediction intervals can be retrieved with the getPredictErr function. - An extended version of the spider dataset has been made available - Added an option to magnify the x-axis labels in coefplot - Site names present as row labels in the response data are now shown in the ordination plot Bug Fixes - The order of the quadratic coefficients was wrong when num.RR, num.lv, and num.lv.c were all used in the same model. - Fixed a bug in the calculation of starting values for constrained ordination (num.RR) where the residuals were not re-calculated if num.lv.c>0 - Fixed a bug in coefplot for when only one predictor was included in the model - Fixed a bug that would prevent using a gllvm with quadratic response model as starting values for another model - Changed import/export of various functions as requested in github issue #65 - Various minor tweaks to the summary function Changes in version 1.3.1 (2021-07-28) New Features - Structured row parameters are implemented, including a possibility for between or within group correlations for random row effects. - Constrained ordination model is implemented. - NB and binomial (with probit and logit) response model implemented using extended variational approximation method. Bug Fixes - Vignettes are removed from the CRAN version of the package, can be seen at the package's website only. New Features - Structured row parameters are implemented, including a possibility for between or within group correlations for random row effects. - Constrained ordination model is implemented. - NB and binomial (with probit and logit) response model implemented using extended variational approximation method. Bug Fixes - Vignettes are removed from the CRAN version of the package, can be seen at the package's website only. Changes in version 1.3.0 (2021-04-30) New Features - Quadratic latent variables allowed, that is term - u_i'D_j u_i can be included in the model using 'quadratic = TRUE'. In addition, functions 'optima()', 'tolerances()' and 'gradient.length()' included. - Beta response distribution implemented using Laplace approximation and extended variational approximation method. - Tweedie response model implemented using extended variational approximation method. - Ordinal model works now for 'num.lv=0'. - Residual covariance adjustment added for gaussian family. Bug Fixes - Estimation of the variances of random slopes of the X covariates didn't work properly when 'row.eff = FALSE' or 'row.eff = "fixed"'. - Problems occurred in calculation of the starting values for ordinal model. - Problems occurred in predict() and residuals(), when random slopes for X covariates were included. - Problems occurred in predict() when new X covariates were given. - Problems occurred in predictLVs() for fourth corner models. New Features - Quadratic latent variables allowed, that is term - u_i'D_j u_i can be included in the model using 'quadratic = TRUE'. In addition, functions 'optima()', 'tolerances()' and 'gradient.length()' included. - Beta response distribution implemented using Laplace approximation and extended variational approximation method. - Tweedie response model implemented using extended variational approximation method. - Ordinal model works now for 'num.lv=0'. - Residual covariance adjustment added for gaussian family. Bug Fixes - Estimation of the variances of random slopes of the X covariates didn't work properly when 'row.eff = FALSE' or 'row.eff = "fixed"'. - Problems occurred in calculation of the starting values for ordinal model. - Problems occurred in predict() and residuals(), when random slopes for X covariates were included. - Problems occurred in predict() when new X covariates were given. - Problems occurred in predictLVs() for fourth corner models.