================
Version 0.3-1
================
NEW FEATURES

   o Function 'cpglmm' is added that handles mixed-effect models using 
	Laplace approximations. This is based on the R package 'lme4'.       
   o Function 'bcpglm' now has a second method to fit Bayesian compound
	Poisson GLM using direct Tweedie density approximation. 
   o Function 'bcpglm' also has a tuning phase that automatically updates
	the scale parameter in the proposal distribution. 
   o The profile likelihood method in 'cpglm' is now automated

CHANGES:
   (user-visible)	
   o Prior distribution of the dispersion parameter in 'bcpglm' is
	changed to be Uniform, specified in the argument 'bound.phi'
   o 'bcpglm' has another argument 'method' that allows users to choose
	from the latent variable approach or direct density evaluation
   o An insurance example 'insLoss' is added in 'bcpglm' 
   o Remove the 'digits' parameter in control in 'cpglm' as the profile 
	likelihood method is automated now 
   o 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. 
   o The default method in 'cpglm' is now set to be 'profile'
   o Remove the 'summary' slot in 'bcpglm'
   o The profile method in 'cpglm' now returns covariance estimate for the 
	dispersion and index parameter 

   (not user-visible):
   o 'bcpglm' replaces ARMS with M-H update. Now the dependency on the 
	ARMS functions is eliminated
   o 'bcpglm' now generates starting values using 'cpglm'
   o Simplify rejection sampling of latent variables (now twice faster)


================
Version 0.2-1
================
NEW FEATURES

   o The package now implements MCMC methods for Bayesian compound 
	Poisson GLM in the function "bcpglm" with the use of 
	latent variables.      
   o 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:
   (user-visible)	
   o Various methods defined for the class "bcplm" and "bcpglm"
   (not user-visible, all in C code):
   o Change the use of "R_alloc" in "lbfgsb" to "Calloc" and "Free" 
	(the old function eats up memory quickly)
   o Simplify rejection sampling of latent variables (now twice faster)

================
Version 0.1-3 (not released)
================
CHANGES (not user-visible, all in C code):
   o Fix a bug in rejection sampling of the latent variable 
   o Fix a bug in specifying weights
   o 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

   o 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:

   o The MCEM algorithm is now implemented in pure C code
   o Remove the restriction on the "weights" argument (but not tested)
   o Add "beta.step" in "control" to allow skips in the update of beta
   o Allow "link" to be both character and numeric
   o Force coercion of argument type before callings the C function
 	- thanks Mikel Esnaola Acebes for pointing out this bug
   o Re-write "summary" and "show" function to produce statistical
	test output automatically
   o Revise "residuals" to allow different types of residuals to be computed
   o Add methods for "formula", "AIC", "deviance", "model.matrix", "terms"
   o Output now returns "deviance", "aic" and "model.frame"
   o Tracing info from MCEM tidied up by showing only the dispersion, the
	index parameter, and the sample size (if necessary)
   o Fix bug in the definition of "[[", add methods for "["