================
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* remove dependency on amer which now is withdrawn from CRAN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 "["