lava 1.8.2 (development version)

• Improved closed testing procedure closed_testing (depr. closed.testing)
• More tests and documentation
• New data deprdiag

lava 1.8.1

• sim.default now accepts the argument R to be a list (of lists) of arguments.
• New methods subset.estimate, transform.estimate, labels.estimate

lava 1.8.0

• New methods estimate.mlm, IC.mlm, pars.mlm, estimate.array, estimate.data.frame
• Print method for tabular data (matrix, data.frame, data.table)
• merge now supports regular expressions
• IC returns row-names (default id) as obtained from model.matrix or similar
• New vignette: Influence Functions
• operators %in.open%, %in.closed% for checking if elements are within a range 3 %in.open% c(0,1))
• estimate(..., estimator='glm') now works with formulas with just an intercept
• as.data.frame.sim, as.matrix.sim
• fixed issues with quasi* families and negative binomial regr (MASS:glm.nb)

lava 1.7.3

• parameter.estimate method to extract matrix with estimates, standard errors, and confidence limits from and estimate object (coefmat element)
• pairwise difference with '-'.estimate and pairwise.diff
• Optional mc.cores arguments to cv and bootstrap
• parameter.lvm now automatically removes previously variables in the lvm object with same name as new added parameters.
• Print function deals more gracefully with non-rectangular objects
• bug-fix in stack.estimate (wrong stand-errors in twostage since version 1.7.0)

lava 1.7.2.1

• Maintenance release as version 1.7.2 broke compatibility with R<4.1.

lava 1.7.2

• Compatibility issues with development version of R fixed.
• cluster.index now also works when not loading the package (directly calling lava::estimate)
• weibull.lvm and coxExponential.lvm now uses default parametrizations similar to rweibull, rexp. weibull.lvm now has arguments “intercept”,“sigma” that directly relates to the accelerated failure time formulation.
• Packages gof, lava.tobit are removed from Suggested packages.

lava 1.7.1

• Fixed bug in variance estimates from estimate with clustered observations.
• Discrete uniform distributions can now be specified with uniform.lvm(value=...).

lava 1.7.0

• cv method moved to the ‘targeted’ package
• New IC method that returns influence function of a model object. The iid argument iid of the estimate method is now replaced with an argument IC (with a user supplied matrix this must now be the actual influence function and not the sample-size scaled version returned by the iid method).
• fixed bug where calls like regression("y", value=function(x) x) did not work. merge.estimate now works without IC element

lava 1.6.10

• Improved starting values for MLE optimization.
• New simulation distributions: multinomial.lvm, none.lvm, constant.lvm, id.lvm.
• regression, regression.lvm: the ‘value’ argument can now be a (non-linear) function specifying the functional relationship between outcomes and covariates (for simulation with the sim method).
• New intervention method for applying interventions on lvm-objects
• Progress updates are now done via the progressr library (enabled with progressr::handlers(global=TRUE)).
• Parallelization is now controlled via the future library. To enable multicore parallelization: future::plan("multicore").
• New plot_region function for adding confidence regions to plots.

lava 1.6.9

• idplot: now accepts matrix or data.frame as 1st argument. New argument: return.data.
• Unit tests updated
• Bug fixes: cv: rmse output fixed. score: Fixed bug for linear Gaussian model with argument ‘indiv=TRUE’. estimate.formula: call object initialized correctly. plot.lvm: ‘noplot’ argument now works with all plot engines.

lava 1.6.8.1

• Maintenance release
• confpred: split-conformal prediction method updated

lava 1.6.8

• Bug-fix: parameter(m,x) now returns an lvm object and not just x
• profile likelihood confidence intervals with tobit/censored observations.
• Vignettes added
  • Estimating partial correlations
  • Non-linear latent variable omdels
• Pseudo-inverse used with “normal” estimator
• Starting values for mixture fixed

lava 1.6.7

• Fixed bug in the composite likelihood complik when used with censored variables (Surv objects).
• Fixed regular expression in ‘spaghetti’ function
• plot.sim: ‘rug’ argument is now by default FALSE and ‘auto.layout’ disabled when nr=nc=1.
• base::sequence() is now a generic function and as a consequence sequence.lvm has been renamed to Sequence.lvm. The function binary.lvm is now an alias of ones.lvm.

lava 1.6.6

• Weighted kmeans++ (wkm). Gaussian mixture models (mvnmix) are now initialized by default using kmeans++.
• sim method implemented for mvnmix models.
• Bug fix: Newton-Raphson method (lava::NR) used a numerical approximation of the Hessian even when submitted as attribute to the objective function.

lava 1.6.5

• Maintenance release.

lava 1.6.4

• New simulation distributions: constant relative risk and risk difference models as in Richardson, Robins and Wang, 2017): binomial.rd, binomial.rr. Base on new hook ‘simulate_multiple_inputs’ which allows the distribution to depend non-linearly on multiple different input variables.
• sim.lvm: ‘X’ argument can now fix (manipulate) any variable and not only exogenous variables.
• Summary function for sim.default updated (the ‘estimate’ argument can now be a list with each element being the estimate position and optionally standard error and true value).
• Starting values updated for mixture models. The parameter names can be obtained with mixture(...,names=TRUE) and set with mixture(...,control=list(start=...))).
• Naming conventions for multigroup parameters: ‘par@g’ (par: name of parameter, g: first group number where ‘par’ is observed). Starting values can be specified with estimate(…,control(list(start=…))).
• New print and summary methods for mixture models.
• Renamed (weighted) K-means function ‘km’ to wkm.
• Derivative method deriv.function based on complex step derivatives.
• twostageCV: estimation of mixture models are now parallelized if mc.cores>1.

lava 1.6.3

• Fixed problems with plots (Rgraphviz)
• Better print method for twostageCV
• Improved M-step in mixture method

lava 1.6.2

• twostageCV: cross-validate two-stage estimator
• rmvn, dmvn moved to mets package (C++ implementation, old versions renamed to lava::rmvn0, lava::dmvn0)
• mediation proportion handled correctly when direct effect is zero
• unit tests clean-up (namespace)
• merge.lvm now correctly handles fixed covariance parameters

lava 1.6.1

• Newton-raphson algorithm made more robust.
• New sim.as method. plot.sim method now by default only plots density estimates
• Compatibility fix with Matrix library

lava 1.6

• Mixture Latent variable models (mixture). Fast version requires ‘mets’ packages; Gaussian mixture models (mvnmix); weighted k-means (km)
• estimate.default: ‘keep’, ‘use’ arguments can be specified as regular expressions (with argument regex=TRUE). Summary method now returns Wald test (null: all parameters being zero).
• makemissing: seed argument added.
• Global change: ‘silent’ argument renamed to ‘messages’
• New utility functions: Grep, Na2x, x2NA, wait, waitclick, rotation, Rot2d, Rot3d
• Condition numbers calculated via SVD
• na.pass0: returns data.frame with original number of rows but with zeros (or first level of factors) in the rows with missing data.
• stack: ‘weights’ argument renamed to ‘propensity’. If propensity=TRUE, the first argument (model) will be treated as propensity score model (glm) and ‘predict’ method will be used for the predictions.
• estimate.formula now by default wraps glm such that the iid method return matrix of same size as full data (with zero rows where data are missing).
• Updated output functions for class ‘sim’ (print method and plot).. Plot method: density.alpha is applied to each standard error (‘se’) level.
• composite likelihood (complik) refactored + new example. ordinal method now cleans up properly when variables are removed (rmvar, subset).
• twostage: fixed for mixture model (class ‘lvm.mixture’). New help page + examples. Predict function updated (newdata argument where covariate levels can be specified).

lava 1.5.1

• conformal predictions: confpred
• warnings (char2num used instead of coersion via as.numeric)
• %++% for function compositon
• New summary.effects methods with mediation proportion in the output
• New hook: remove.hooks (see example ordinal.lvm)
• constrain methods now handled more robustly in sim.lvm allowing both vectorized and non-vectorized functions
• Non-linear associations can now be specified with nonlinear method. Estimation via the twostage function.
• Robust standard errors added to the IV estimator (2SLS)
• New cross-validation function: cv (and csplit function for creating random sets).

lava 1.5

• lava.tobit is longer required for ordinal and censored responses. Default is now to use the implementation in the ‘mets’ package.
• Composite likelihood method (complik) updated
• weight argument renamed to weights in agreement with lm, glm, coxph, …
• sim.default: new argument ‘arg’ passed on to simulation function
• sim.default: new argument ‘iter’. If TRUE the iteration number is passed to function call as first argument (default FALSE)
• estimate.default: Wildcards/global expressions can now be used for specifying contrasts based on the syntax of the functions contr, parsedesign. See examples on the help-page. The argument transform.ci has been renamed to back.transform.
• correlation methods for matrices and data.frames (either pairwise or full MLE). All methods can now return the influence functions.
• revdiag: dimnames are kept
• Combine: output updated
• forestplot: point estimates shown by default
• backdoor now works without conditioning set (yields all possible conditioning sets)
• New formula syntax: y+x~v+z same as c(y,x)~v+z
• spaghetti: trend.formula can now contain a factor statement on the rhs

lava 1.4.7

• Maintenance release
• models can now be specified as y1+y2~x1+x2 instead of c(y1,2y)~x1+x2
• sim method now has a seed argument

lava 1.4.6

• New backtrace algorithms for Newton-Raphson optimization routine (NR).
• diagtest updated.

lava 1.4.5

• New graph functions: dsep: check for d-separation (conditional independence). backdoor: check backdoor criterion of a graph (lvm-object). adjMat: return adjaceny matrix. edgeList: return edge list. ancestors: return ancenstors of nodes. descendants: return descendants of nodes.
• All simple paths in a graph can now be extracted with: path(...,all=TRUE)
• Covariance parameters are now reference with ~~ instead of ,. Applies to setting starting values in estimate, parameters in sim,compare,estimate,… To use the old syntax set lava.options(symbol=c("~",",")).
• layout argument added to lava.options (default ‘dot’)
• visNetwork support, new plot.engine argument added to plot methods.
• bootstrap.lvmfit now default returns original estimates.
• print, transform methods updated (transform output).
• + operator overloaded for lvm and estimate objects (merge).
• New composite likelihood function: complik.
• New functions for simple association measures: riskcomp, rdiff, rratio, …
• New argument ‘latent’ in simulate method. If FALSE the latent variables are dropped from the returned data.frame.
• modelsearch by default now shows both directional or undirectional associations (type=‘all’ vs type=‘cor’).
• sim.default now stores timings. New print functions (data.table like output).
• lvm model can now be updated with the sim function, for instance setting parameter values for the simulation only once: m <- sim(m,p=p,...), with faster subsequent calls sim(m,n=n).
• estimate.default can now simulate p-values (‘R’ argument). Returns an object which can also be used as input for estimate.
• Bug fixes: NR optimization with back-tracing; fixed matrices.lvm when called without variance parameters; fixed a bug in r-square computations.
• Contrast matrix can be specified with the function contr.

lava 1.4.4

• estimate.default will now use the id-variable of an ‘estimate’ object if the ‘id’ argument is left unspecified. For multinomial,gkgamma,kappa additional arguments (…) are now parsed on the ‘estimate.default’ (including id).
• Updated print/summary methods for ‘estimate.default’. Sample/cluster-size added to output.
• Code clean-up and optimization. Smarter calculations of kronecker products, and some regular expressions updated.
• New function ‘predictlvm’ which return jacobian.
• Intercepts can now be specified via parantheses, e.g., y ~ (-2) + x
• ‘getoutcome’ with sep argument for splitting ‘|’ statements in formulas.
• Partial gamma, gkgamma, updated (probability interpretation, homogeneity tests removed)
• ‘moments’ function now returns conditional mean with multiple rows. Side effect fixed across multiple functions
• twostage function with support for mixture models
• Beta (Beta.lvm) and Finite Gaussian (GM2.lvm,GM3.lvm) Mixtures added.
• ‘sim’: parameters can now be specified as part of ‘…’
• summary.sim: calculate Wald CI if confint=TRUE, otherwise use the user supplied confidence limits.
• Clopper-pearson intervals and exact binomial tests added to ‘diagtest’.
• Interval censoring with ‘normal’ estimator, which now also works with ‘binary’ definitions.
• default plot style updated.

lava 1.4.3

• partial gamma coefficients (gkgamma)
• Unit tests works with new testthat version
• Avoid trying to fork new processes on windows (bootstrap,sim.default)

lava 1.4.2

• Code optimization and minor bug fixes
• Travis-CI, unit-tests
• glm estimator update (censored regression)
• polychoric correlations (pcor)
• New utility functions: wrapvec, offdiag
• simulation: regression design on parameters (see weibull + variance hetereogeneity example in help(‘sim’))
• Byte compile by default

lava 1.4.1

• New plot.estimate method
• Documentation and examples updated

lava 1.4.0

• Linear measurement error model: ‘measurement.error’
• Diagnostic tests: ‘diagtest’
• ‘plotConf’ updated with support for special function terms (I, poly, ns, …). Old version is available (not in namespace) as lava:::plotConf0
• Pareto distribution: ‘pareto.lvm’
• Code clean-up/optimization: ‘EventTime’, ‘stack’
• ‘estimate.default’ new syntax for contrast specification (parsedesign)
• ‘regression.lvm’ with y,x argument (as alias for to,from)
• plot longitudinal data: ‘spaghetti’
• Examples updated

lava 1.3

• New syntax for categorical predictors (method ‘categorical’ and argument ‘additive=FALSE’ with ’regression method)
• Argument ‘intervals’ added to ‘ones.lvm’ for piece-wise constant effects
• Argument ‘average=TRUE’ now needed for empirical averages in estimate.default
• Fixed a bug in score.glm (with weights and offset) introduced in version 1.2.6
• estimate.default:
  • small-sample corrections
  • Default id from row names in estimate.default (used with merge method)
  • iid decompostion also returned for hypothesis contrasts
  • keep argument added to estimate.default and merge
  • labels argument added to estimate.default
• ‘images’ function for visualization of tabular data added to namespace
• ‘ksmooth’ and ‘surface’ for surface estimation and visualization of bivariate data and functions
• ‘dsort’: Sort data.frames
• general multivariate distributions in simulations. see example in ‘sim’
• ‘or2prob’, ‘tetrachoric’ for conversion from OR to probabilities (and tetrachoric correlations). ‘prob.normal’: calculates probabilities from threshold model given thresholds and variance See also mets:::assoc for calculations of kappa, gamma, uncer.coef. ‘normal.threshold’: returns thresholds,variance,mu from model with categorical outcomes.
• Multiple testing routines: closed.testing, p.correct, …
• ‘Missing’ method updated with a simple ‘suffix’ argument
• Back-tracing updated in Newton-Raphson routine

lava 1.2.6

• New ‘stack’ function for two-stage estimation (via ‘estimate’ objects)
• New ‘blocksample’ function for resampling clustered data.
• New function ‘Missing’ to generate complex missing data patterns
• Weibull parametrization of ‘coxWeibull.lvm’ rolled back (ver. 1.2.4). The function ‘weibull.lvm’ now leads to Accelerated Failure Time model (see examples of ‘eventTime’)
• iid function cleanup (new ‘bread’ attribute). iid.glm now gives correct estimated influence functions for ‘quasi’ link (constant variance)
• Parameter constraints on (co)variance parameters now possible with the syntax lvm(…,y~~a*x) (corresponding to covariance(…,y~x)<-“a”)
• Some additional utilities: pdfconvert, scheffe, images, click. confband updated with ‘polygon’ argument.
• New function getMplus: Import results from Mplus
• New function getSAS: Import SAS ODS
• New ‘edgecolor’ argument of plot-function

lava 1.2.5

• ‘merge’ method added for combining ‘estimate’ objects
• Adjustments to starting values
• Function ‘categorical’ for adding categorical predictors to simulation model
• Improved flexibility in simulations with ‘transform’,‘constrain’ (ex: categorical predictors)
• Added ‘dataid’ argument to estimate.default allowing different id for ‘data’ and i.i.d. decomposition of model parameter estimates. With the argument ‘stack=FALSE’ influence functions within clusters will not be stacked together.
• R-squared values (+ approximate standard errors/i.i.d. decomposition) via ‘rsq(model,TRUE)’
• New infrastructure for adding additional parameters to models (no user-visible changes).
• multinomial function for calculating influence curves for multinomial probabilities. ‘gammagk’ and ‘kappa’ methods for calculating Goodman-Kruskals gamma and Cohens kappa coefficients.
• ordreg function for univariate ordinal regression models
• iid methods for data.frames/matrices (empirical mean and variance)
• Support for using ‘mets::cluster.index’ in GEE-type models (much faster).
• plotConf updated (vcov argument added and more graphical arguments parsed to plotting functions)
• Additional unit-tests implemented
• New ‘forestplot’ and ‘Combine’ functions
• Covariance structure may now be specified using ‘’, e.g. ’lvm(c(y,v)z+u)’ specifies correlation between residuals of (y,z),(y,u),(v,z),(v,u).

lava 1.2.4

• Avoid estimating IC in ‘estimate.default’ when ‘vcov’ argument is given.
• New default starting values
• Time-varying effects via ‘timedep’
• R-squared added to summary
• alias: covariance->variance
• added size argument to binomial.lvm;

lava 1.2.3

• ‘subset’ argument added to estimate.default. Calculates empirical averages conditional on subsets of data
• Improved output from compare/estimate functions
• Minor bug fixes (plot, predict)
• sim: Piecewise constant rates with coxEponential.lvm. New aalenExponential.lvm function for additive models. Functions ones.lvm and sequence.lvm for deterministic variables.

lava 1.2.2

• Regression parameters are now by default referenced using ‘~’, e.g. “y~x” instead of “y<-x”. Applies to setting starting values in ‘estimate’, parameters in ‘sim’,‘compare’,‘estimate’,…. To use the old syntax set ‘lava.options(symbol=c(“<-”,“<->”))’
• Newton-Raphson/scoring procedure updated
• Search-interval for profile likelihood CI improved (for variance parameters)
• ‘estimate.default’ updated (LRT)
• ‘iid’ updated (variance now obtained as tensor product of the result)
• progress bar for ‘bootstrap’ and ‘modelsearch’
• various minor bug fixes
• new functions: Expand (expand.grid wrapper), By (by wrapper)

lava 1.2.1

• Optimization + minor bug fixes

lava 1.2.0

• New method ‘iid’ for extracting i.i.d. decomposition (influence functions) from model objects (e.g. glm, lvm, …)
• Method ‘estimate’ can now be used on model objects to transform parameters (Delta method) or conduct Wald tests. Average effects, i.e. averaging functionals over the empirical distribution is also possible including calculation of standard errors.
• ‘curereg’ function for estimating mixtures of binary data.
• Instrumental Variable (IV) estimator (two-stage least-squares) optimized.
• New distributions: Gamma.lvm, coxWeibull.lvm, coxExponential.lvm, coxGompertz.lvm. New method ‘eventTime’ (for simulation of competing risks data)