================ Version 0.7-10 ================ CHANGES: * Fix issues related to USE_FC_LEN_T ================ Version 0.7-9 ================ CHANGES: * Remove zcpglm * Allow compatibility with changes in statmod ================ Version 0.7-5 ================ CHANGES: * ‘gini’ now can handle a single score * Fixed bug when supplying initial values ================ Version 0.7-4 ================ CHANGES: * 'predict' method failed when 'cpglm' is rank deficient. Fixed this. Now returns the prediction but with a warning. * 'predict' method for 'cpglmm' defaults to type = 'response'. * Fix issues when specifying initial values for 'bcplm' * Add author info for the 'amer' functions * Update vignettes ================ Version 0.7-3 ================ CHANGES: * update to be compatible with R 3.x (Prior versions failed) ================ Version 0.7-2 ================ CHANGES: * fix bug related to sp2d ================ Version 0.7-1 ================ CHANGES: * remove dependency on lme4 which is now completely re-written ================ Version 0.6-4 ================ CHANGES: * remove dependency on amer which now is withdrawn from CRAN ================ Version 0.6-1 ================ NEW FEATURES * Add vignettes * Add function 'zcpglm' which implements a zero-inflated compound Poisson generalized linear model * Add function 'gini' which computes the Gini indices that enable robust model comparison involving compound Poisson distributions CHANGES: * Add a new data set 'AutoClaim' * Set the max number of terms in computing the compound Poisson density using series evaluation method. * Correct bugs in predicting 'cpglm'. When the new data set has fewer factor levels, the old method produces wrong predictions. * 'cpglm' has an argument 'optimizer' that allows users to select optimization routines. * Function 'bcplm' now implements MCMC methods for both GLM and mixed models. This is a combination of the old functions 'bcpglm' and 'bcpglmm' * Produce model summary for Bayesian estimates (from 'bcplm') * Provide methods 'fixef' and 'VarCorr' for class 'bcplm' * The tuning procedure in MCMC is now based a method described in Browne and Draper (2005) * MCMC now only implements univariate M-H within Gibbs sampling. Block update for the fixed effects are removed. * Remove the latent variable approach for Bayesian estimation * Remove method 'mcmcsamp' * Functions 'getF' and 'plotF' (copied from 'amer') now works for additive models to extract and plot fitted smoothing effects * Fix bugs in quadrature estimation of mixed models due to code inherited from lme4. This will only affect models with multiple random effects per level. * Fix the underflow issue in the quadrature estimation. * Implement the PQL method to generate initial values in 'cpglmm'. ================ Version 0.5-1 ================ NEW FEATURES * Methods 'mcmcsamp' now is not available for 'cpglm' and 'cpglmm' objects as a convenient way to perform MCMC simulations. * Function 'cpglmm' handles additive models in a similar way as the package 'amer'. * Big data capability is added to function 'cpglm', which uses the bounded memory regression facility from the package 'biglm'. * Function 'cpglmm' has an additional argument 'optimizer' that allows the users to choose which optimization routine to be used. The package 'minqa' is now imported for the use 'bobyqa'. * Function 'cpglmm' now implements adaptive Gauss-Hermite quadrature method for models with a single grouping factor. * Function 'bcpglmm' now implements an additional latent variable approach. CHANGES: * The MCEM method is now completely removed from 'cpglm' * In 'cpglmm', the Laplace approximated loglikelihood seems to have left out the dispersion parameter for one term, resulting a larger than expected variance component estimate. This is now fixed and it is more consistent with the quadrature estimate. * Add method 'predict' for 'cpglm' and 'cpglmm', which computes the predicted values for a new data set, but not the prediction errors. * In 'cpglmm', fix a bug in specifying 'offset' * In 'cpglmm', 'sigmaML' is updated after fitting the model so that the 'postVar' option in 'ranef' in 'lme4' can be used now. * 'weights' was not reflected in the update of the deviance. This is fixed now. * In 'cpglmm', 'vcov' now computes variances for 'phi' and 'p' * register native routines in initialization ================ Version 0.4-1 ================ NEW FEATURES * Function 'bcpglmm' is added that handles Bayesian mixed-effect models using MCMC simulations. CHANGES: * create the class 'cplm' as a fundamental structure in the package, and define utility methods for it * replace the 'pstart', 'phistart' and 'betastart' arguments by a single argument 'inits' in most functions * combine the documentation for all classes and methods ================ Version 0.3-1 ================ NEW FEATURES * Function 'cpglmm' is added that handles mixed-effect models using Laplace approximations. This is based on the R package 'lme4'. * Function 'bcpglm' now has a second method to fit Bayesian compound Poisson GLM using direct Tweedie density approximation. * Function 'bcpglm' also has a tuning phase that automatically updates the scale parameter in the proposal distribution. * The profile likelihood method in 'cpglm' is now automated CHANGES: * Prior distribution of the dispersion parameter in 'bcpglm' is changed to be Uniform, specified in the argument 'bound.phi' * 'bcpglm' has another argument 'method' that allows users to choose from the latent variable approach or direct density evaluation * An insurance example 'insLoss' is added in 'bcpglm' * Remove the 'digits' parameter in control in 'cpglm' as the profile likelihood method is automated now * MCEM method in 'cpglm' simplifies the process of increase sample size. The old time-consuming method of estimating approximate covariance matrix is removed. So the 'alpha' parameter in control is removed. * The default method in 'cpglm' is now set to be 'profile' * Remove the 'summary' slot in 'bcpglm' * The profile method in 'cpglm' now returns covariance estimate for the dispersion and index parameter * 'bcpglm' replaces ARMS with M-H update. Now the dependency on the ARMS functions is eliminated * 'bcpglm' now generates starting values using 'cpglm' * Simplify rejection sampling of latent variables (now twice faster) ================ Version 0.2-1 ================ NEW FEATURES * The package now implements MCMC methods for Bayesian compound Poisson GLM in the function "bcpglm" with the use of latent variables. * The R package "coda" is imported so that a large number of functions and methods defined there are now directly applicable to the simulation results from "bcpglm" to help diagnose convergence and summarize posterior inference. CHANGES: * Various methods defined for the class "bcplm" and "bcpglm" * Change the use of "R_alloc" in "lbfgsb" to "Calloc" and "Free" * Simplify rejection sampling of latent variables (now twice faster) ================ Version 0.1-3 ================ CHANGES: * Fix a bug in rejection sampling of the latent variable * Fix a bug in specifying weights * Divide cpglm_str into three parts, one for data and parameters, one for latent variable, and one for EM related ================ Version 0.1-2 ================ NEW FEATURES * Add a wrapper of the profile likelihood approach to the "cpglm" function that runs automatically to generate estimate of the index parameter to arbitrary accuracy. CHANGES: * The MCEM algorithm is now implemented in pure C code * Remove the restriction on the "weights" argument (but not tested) * Add "beta.step" in "control" to allow skips in the update of beta * Allow "link" to be both character and numeric * Force coercion of argument type before callings the C function - thanks Mikel Esnaola Acebes for pointing out this bug * Re-write "summary" and "show" function to produce statistical test output automatically * Revise "residuals" to allow different types of residuals to be computed * Add methods for "formula", "AIC", "deviance", "model.matrix", "terms" * Output now returns "deviance", "aic" and "model.frame" * Tracing info from MCEM tidied up by showing only the dispersion, the index parameter, and the sample size (if necessary) * Fix bug in the definition of "[[", add methods for "["