Changes in Version 0.10
- ml_tsdlvm1 now orders data by idvar if beepvar is not supplied.
- Added 'CIplot' function
- Standardizing in ts_dlvm1 is now more stable.
- dlvm1 now uses observed variable names as latent variable names when appropriate.
- Fixed a bug with the beepvar argument in psychonetrics
Changes in Version 0.9:
- Changed 'rel.tol=1e-10' in the nlminb optimizer to be in line with lavaan
- Added 'warn_improper' argument to runmodel(..)
- The argument 'return_improper' now defaults to TRUE
- Optimizer no longer uses a spectral shift when inverting a semi-positive definite matrix
- Detection of non positive definite matrices is now done faster and should lead to less problems
- The default optimizer is now cpp_L-BFGS-B!
- Added the 'bounded' argument to runmodel() to define if bounded estimation should be used (defaults to TRUE)
- Diagonals of symmetrical matrices can no longer be estimated to be negative (avoiding Heywood cases, although doing this with a Cholesky decomposition is nicer!)
Changes in Version 0.8.1:
- The nlminb estimator now uses more iterations.
Changes in Version 0.8:
- The log determinant is now computer better to be able to include fit measures at higher model complexities
- The 'return_improper' argument in runmodel( ) now returns improper estimates without trying different starting values
- Fixed a bug in meta_varcov when using individual estimates of the sampling variation
- Updated optimizer default control parameters
Changes in version 0.7.6:
- Model estimations that used improper estimation (pseudoinverse of variance-covariance matrix) now return with an error unless return_improper = TRUE in runmodel()
- Equality-free MIs are now also computed when all edges are included
Changes in version 0.7.5:
- Fixed a bug with nu_zeta being constrained in multigroup LGC models.
- factorscores now supports multi group models
Changes in version 0.7.3:
- Added the 'covariates_as' argument to latentgrowth() to model covariates with regressions (now default) or covariances
Changes in version 0.7.2:
o Fixed a bug with removing diagonal elements of sigma_epsilon with single indicators
o Fixed another bug with models with only one free indicator
o Added the partialprune function for partially pruning multi-group models
Changes in version 0.7.1:
o Fixed a bug for Solaris
Changes in version 0.7:
o Major changes
o Major restructuring of underlying core code. Most vital functions have been translated to C++, leading to a large speedup!
o Added C++ based optimizers cpp_L-BFGS-B, cpp_CG, cpp_SANN, and cpp_Nelder. These are faster but slightly less stable than nlminb (now the default optimizer).
o Verbose now defaults to FALSE everywhere. This can be set with the setverbose function for a model
o Added meta-analysis model for varcov family (meta_varcov)
o The ml_tsdlvm1 function now allows for multi-kevek tsdlvm1 models (dlvm1 models) to be specified using syntax familiar to those using mlVAR and graphicalVAR
o Minor changes
o Numerous small bugfixes and improvements (e.g., better starting values)
o Added function 'fullFIML' to use true FIML computing the likelihood per row
o Changed 'WLS.V' to 'WLS.W'
o Several warning messages have been updated
Changes in version 0.6:
o The 'dlvm1' model family now also returns the implied latent variance-covarriance matrix as 'sigma_eta_within'
o The latent lag-1 matrix is also returned as 'sigma_eta_within_lag1'
o The dlvm1 model family now no longer requires a 'lambda' matrix to be specified (will default to a panelvar model)
o Most model families now support the 'standardized' argument, which can be set to 'z' for z-scores (helps convergence) or 'quantile' for a semiparametric transformation
o Added the ml_lvm family for two-level random intercept latent variable models
o Added the simplestructure function to easily make a lambda matrix
o addalpha in modelsearch now works as expected
o addalpha and prunealpha now default to 0.01 in 'modelsearch'
o recursive now defaults to FALSE in 'prune'
Changes in version 0.5.1:
o Fixed a bug with responses being missing when summary statistics are used in Ising()
o Fixed a bug with covtype sometimes being set to UB when corinput = TRUE
o Added DOI to description field
Changes in version 0.5.0:
o The Ising model is now supported (only ML estimation) through the Ising() model function
o Added the covtype option to several models, controlling if maximum likelihood or unbiased estimates are used for the input covariances
o Added the function 'covML' for maximum likelihood covariance estimates
Changes in version 0.4.1:
o Small fix for CRAN checks
Changes in version 0.4:
o type = "cor" is now supported in varcov, with rho representing the correlations and SD the diagonal standard deviations matrix.
o The 'corr' function is now implemented as shorthand for varcov(..., type = "cor")
o The scale of the Fisher information matrix has been adjusted to portray unit information to be similar to Lavaan
o The getVCOV function has been added to obtain the estimated asymptotic var-cov matrix of the parameters.
o The meanstructure can now be ignored using meanstructure = TRUE in the following model families:
- varcov
o A correlation matrix can now be used as input (detected or set with corinput = TRUE) for the following families:
- varcov (type = "ggm" and type = "cor")
o The WLS estimator will now not investigate means when meanstructure is ignored, and variances when a correlaton matrix is used as input.
- The WLS weights matrix must be of the appropriate dimensions!
- The WLS.V matrix will no longer be adjusted for missing means.
- Added 'startEPC' argument to stepup and freepar
o Added the 'modelsearch' function for extensive stepwise model search
o Fixed several bugs and improved starting values in several models
Changes in version 0.3.3:
o prune() now removes diagonal values of temporal effects
o psychonetrics now requires R 3.6
o Some C++ fixes for Solaris
Changes in version 0.3.2:
o The parameters function now invisibly returns the parameter estimate data frame
o The MIs function now invisibly returns a data frame with MI estimates
o fit now invisibly returns a data frame with fit measure estimates
Changes in version 0.3.1:
o Several help-files are now updated with executable examples
Version 0.3.0: First version to be submitted to CRAN