Changes in flexmix version 2.2-4 o Model drivers FLXMRlmer() and FLXMRlmm() added for fitting finite mixtures of linear mixed effects models. o EIC() added as additional information criterion for assessing model fit. o Bug fixed in plot method for flexmix objects introduced in version 2.2-3. Changes in flexmix version 2.2-3 o New model driver FLXMCmvcombi() which is a combination of Gaussian and binary. o parameters() now also has a which argument in order to allow to access the parameters of the concomitant variable model. o Bug fixed in refit(). o nobs() now returns the number of rows in the data.frame and not the number of individuals (similar as for example by lme). Changes in flexmix version 2.2-0 o vignette describing Version 2 added o isTRUE(all.equal()) replaced with identical(). o Bug fixed for prior in flexmix(). o New function relabel() to sort components (generic is in modeltools). o New example data generator ExLinear(). o Fixed a bug in handling groups (gave an error for empty design matrices). o Added new model FLXMRrobglm() for robust estimation of GLMs. Changes in flexmix version 2.1-0 o Renamed cluster() to clusters() to avoid conflict with cluster() from package survival o Bug fixed in internal functions using S4 generics and methods. Changes in flexmix version 2.0-2 o refit() now has a method argument. For method "optim" the variance-covariance matrix is determined using optim() to maximize the likelihood initialized in the solution found by the EM algorithm. Method "mstep" refits the component specific and concomitant models treating the posterior probabilities as given, i.e. performs an M-step of the EM algorithm. Changes in flexmix version 2.0-1 o Lapply() added which allows to apply a function to each component of a finite mixture o KLdiv() modified to allow for determination with a discrete and a continuous version of the KL divergence Changes in flexmix version 2.0-0 o Model driver for zero-inflated component specific models. o Latent class analysis for binary multivariate data is now possible to estimate for truncated data where the number of observations with pattern only zeros is missing. o new argument newdata for cluster() o new unique() method for "stepFlexmix" objects Changes in flexmix version 1.9-0 o New class definitions for component specific models and concomitant variable models. o fitted() and predict() now have an aggregate argument in order to be able to determine the aggregated values over all components. o The package has now a vignette presenting several applications of finite mixtures of regression models with varying and fixed effects on artificial and real data which can be a accessed using the command vignette("regression-examples"). o The vignette "flexmix-intro" was adapted to reflect the changes made in the package. o stepFlexmix() now returns an object of class stepFlexmix which has a print and plot method. In addition getModel() can be used to select an appropriate model. o flexmix() now has a weights argument for multiple identical observations. o New model drivers for latent class analysis with Bernoulli and Poisson distributed multivariate observations. o Variants of the EM algorithm have been modified to correspond to CEM and SEM. These names can now also be used for specifying the classify slot of the FLXcontrol object. Changes in flexmix version 1.8-1 o The package can now fit concomitant variable models. o New M-step driver for regression models with varying and fixed effects. o ICL information criterion Changes in flexmix version 1.1-2 o Fixed a bug that made the log-likelihood infinity for observations where all posteriors are numerically zero o Fixed a bug for formulae with dots. o posterior() now has a newdata argument. o New demo driver for model-based clustering of binary data. o Adapted to changes in summary.glm() of R version 2.3.0. Changes in flexmix version 1.1-1 o The 'cluster' argument of flexmix() may now also be a matrix of posterior probabilities. o Fixed a bug to make size table work in case of empty clusters. o Fixed a bug in likelihood computation for grouped observations. o The artificial NPreg data now also have a binomial response, added example to help("flexmix"). Changes in flexmix version 1.1-0 o The FLXglm driver now has an offset argument. o New data set seizure as example for a Poisson GLM with an offset. o fitted() can be used to extract fitted values from flexmix and FLXrefit objects. o New accessor methods cluster() and posterior(). o The package now uses lazy loading and has a namespace. Changes in flexmix version 1.0-0 o The package has now an introductionary vignette which can be accessed using the command vignette("flexmix-intro"). The vignette has been published in the Journal of Statistical Software, Volume 11, Issue 8 (www.jstatsoft.org), and the paper should be used as citation for flexmix, run citation("flexmix") in R 2.0.0 or newer for details. o Several typos in help pages have been fixed. Changes in flexmix version 0.9-1 o Adjust for R 2.0.0. o Fixed a bug in the summary and plot methods of flexmix objects in case of empty clusters. o stepFlexmix takes two new arguments: `compare' allows fo find minimum AIC/BIC solutions in addition to maximum likelihood, `verbose' gives some information about progress. o Use a default of verbose=0 in FLXcontrol (better in combination with stepFlexmix). Changes in flexmix version 0.9-0 o new summary() and plot() methods for flexmix objects o FLXglm objects can now be automatically refit()ted to get table of significance tests for coefficients o new function stepFlexmix() for more automated model search o the artificial example data now have functions to create them and a pre-stored data sets, new function plotEll() to plot 2d Gaussians with confidence ellipses. o new function KLdiv() to compute Kullback-Leibler divergence of components o the calculation of the degrees of freedom for FLXmclust was wrong Changes in flexmix version 0.7-1 o fixed some codoc problems (missing aliases) First version released on CRAN: 0.7-0