coencliner Change Log

Version 0.2-3

	* Fix an issue related to an upgrade to the *hyperref* LaTeX
	package that was causing vignette compilation to fail.
	Reported by: Brian Ripley.

Version 0.2-2

	* Fix bug in `NegBin()` and `ZINB()` which had incorrect
	specification of the gamma mixture part of the distribution.
	Reported by: @nlhuong #24

	* Allow for vector `alpha` in `NegBin()` and `ZINB()`

Version 0.2-1

	* Fix problems identified by `R CMD check` under R-devel

Version 0.2-0

	* Bug Fix: A typo in the bivariate Beta response function led
	to the code ignoring `gamma` for the second gradient, which
	used the value for first gradient instead.
	Reported by: Jari Oksanen (with patch/fix)

	* For additional details, please see the github commit log:
	http://github.com/gavinsimpson/coenocliner/commits/master

	For higher-level news of chanegs to the package, see the NEWS
	file.

Version 0.1-0

	* Released to CRAN...

Version 0.0-10

	* Gaussian: default for `corr` changed to `0` so users don't
	need to specify this unless they want correlated responses.

	* vignette: added a basic tutorial vignette document to the
	package.

	* BetaBinomial: realised I should have asked Jari for
	permission to copy code to compute the parameters of the
	beta distribution from a parameter tau^2. This came from his
	BETASIMU C code. I've temporarily removed this code until such
	a time as I get permission to include it (Jari is in the field).
	I've replaced it with a different parameterisation I found in
	Ben Bolker's Ecological Models and Data in R book.

Version 0.0-9

	* ZIP, ZINB: new wrappers for random number generation for the
	zero-inflated Poisson (ZIP) and Negative binomial (ZINB)
	distributions. These functions are simple ZIP and ZINB
	distributions where the probability of a zero from the binomial
	part of the model depends only on a mean probability of zero.

Version 0.0-8

	* Binomial, BetaBinomial: New wrappers for random number
	generation for the Binomial and Beta-Binomial distributions.
	The Binomial distribution allows simulation of binomial counts
	from a probability of occurence and binomial denominator, m,
	the number of trials (number of individuals counted).

	The Beta-Binomial() is an extra-variance Binomial distribution
	and allows simulation of overdispersed binomial count data in a
	manner similar to that by which the Negative binomial
	distribution can be used to generate overdispersed Poisson
	count data.

Version 0.0-7

	* Beta: now implemented for one or two gradients.

Version 0.0-6

	* Binomial(): this really should have been Bernoulli and now is.

Version 0.0-5

	* Old code: This version removed all the `simxDfoo()` functions
	and associated helpers (`betaResponse()`, `gaussianResponse()`,
	`biGaussianResponse()`, `expandGauss()`, `expandBeta()`) as
	these are now no longer needed given that we have `coenocline()`
	as a gneral interface to all these things.

Version 0.0-4

	* Gaussian() & Beta() modified to take lists of arguments, `px`
	and `py`, to simplify the naming of species parameters in these
	models.

	* coenocline() modified to supply arguments in the format now
	required by `Gaussian()` and `Beta()`.

Version 0.0-3

	* coenocline() a generic interface to coenocline simulation.

	* Beta(), Gaussian(); new response model functions for the
	classic Gaussian response model and the generalised Beta
	response model.

	* New wrappers for random deviate generation from Poisson,
	Binomial, and Negative binomial distributions.

	* expand() a new general version of the expand.grid()-like
	functionality where we repeat sets of parameters for each of
	n gradient locations.

Version 0.0-2

	* added simulators for occurrence not abundance
	Code provided by F. Rodriguez-Sanchez.

Version 0.0-1

	* intial alpha version
