Version 2.0.10
=============

* CRAN update version 2.0.10
* See updates in 2.0.6-2.0.10

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.

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

Version 2.0.7
=============

* Mixed response type model implemented
* Added simulated confidence intervals to predict.gllvm, see #24

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

Version 2.0.5
=============

* 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

Version 2.0.4
=============
* Logit and cumulative logit models with method = "VA"

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

Version 2.0.2
=============

## 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

Version 2.0.1
=============

* 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

Version 2.0
=============

* For CRAN release 2.0 see updates for versions 1.4.4 - 1.4.9

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

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

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)

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

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

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

Version 1.4.3
==============
* 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

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

Version 1.4.1
==============

### 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

Version 1.4.0
==============

### 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

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

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

Version 1.3.1
==============

### 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.


Version 1.3.0
==============

### 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.

Version 1.3.1
==============

### 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.


Version 1.3.0
==============

### 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.

