Title: Conway-Maxwell-Poisson GLM and distribution functions
Description: The package contains a function (which uses a similar interface to
the `glm' function) for the fitting of a Conway-Maxwell-Poisson GLM. There
are also various methods for analysis of the model fit. The package also
contains functions for the Conway-Maxwell-Poisson distribution in a similar
interface to functions `dpois', `ppois' and `rpois'. The functions are
generally quick, since the workhorse functions are written in C++ (thanks

Title: Conway-Maxwell-Poisson GLM and Distribution Functions
Description: A function (which uses a similar interface to the `glm' function)
for the fitting of a Conway-Maxwell-Poisson GLM. There are also various
methods for analysis of the model fit. The package also contains functions
for the Conway-Maxwell-Poisson distribution in a similar interface to
functions `dpois', `ppois' and `rpois'. The functions are generally quick,
since the workhorse functions are written in C++ (thanks to the Rcpp
Suggests: testthat, devtools, roxygen2, covr, lintr

Description: Computes the probability density function, cumulative
distribution function, quantile function, random numbers and
maximum likelihood estimates of any composite model based on

distribution function, quantile function, random numbers of any
composite model based on the lognormal distribution.

Description: Computes the probability density function, cumulative distribution function, quantile function, random numbers of any composite model based on the lognormal distribution.

Title: Pseudo Computer Models for Optimization
Description: A suite of computer model test functions that can be used to test and evaluate algorithms for Bayesian (also known as sequential) optimization. Some of the functions have known functional forms, however, most are intended to serve as black-box functions where evaluation requires running computer code that reveals little about the functional forms of the objective and/or constraints. The primary goal of the package is to provide users (especially those who do not have access to real computer models) a source of reproducible and shareable examples that can be used for benchmarking algorithms. The package is a living repository, and so more functions will be added over time. For function suggestions, please do contact the author of the package.