- Allows marginal likelihood calculations via power posterior in
`mcmc_pol()`

(for the polylog distribution) and`mcmc_mix2()`

(for the 2-component mixture distribution). The combination of the existing argument`invt`

for inverse temperatures and the new boolean argument`mc3_or_marg`

determines either parallel tempering or power posterior or neither will be performed. - The corresponding wrapper functions are updated accordingly.

- Add
`marg_pow()`

for calculating the posterior density and marginal (log-)likelihood of the discrete power law i.e. the Zipf distribution. - Change
`update()`

in C++ in preparation for marginal log-likelihood calculations for other models (Zipf-polylog, mixtures, etc.)

- Calculations using
`marg_pow()`

added to align with`mcmc_pol()`

(when theta = 1.0) in terms of posterior density.

- The argument
`name`

has been removed in the wrapper functions as it required data frames with a specific column`name`

. - Functions related to the TZP-power-law mixture model (mid-way of current 2-component & 3-component mixtures) are added.
- Wrapper functions of the 2-component & 3-component mixtures have the default arguments included in the body so they are relayed to
`obtain_u_set_mix2()`

or`obtain_u_set_mix3()`

.

- The default value of
`s_alpha`

in`mcmc_mix3_wrapper()`

is changed from 0.0 to 10.0. - In
`obtain_u_set_mix3()`

, whether there is data between v & u is checked before optimisation. This prevents a warning when the “Brent” method is used (when only alpha is optimised as theta is fixed to 1.0), when there’s no data points between v & u. - In
`dpol()`

&`Spol()`

, the check for alpha <= 1.0 is made only when theta == 1.0 i.e. the power law applies.

- README.md is updated.

- Added are
`obtain_u_set_mix2()`

and`obtain_u_set_mix3()`

, which are functions for obtaining the profile posterior density for the 2-component and 3-component mixture models, respectively. - Also added thin wrappers for
`mcmc_pol()`

,`mcmc_mix2()`

and`mcmc_mix3()`

, all with the suffix`_wrapper`

. Specifically,`mcmc_mix2_wrapper()`

calls`obtain_u_set_mix2()`

and`mcmc_mix2()`

, and`mcmc_mix3_wrapper()`

calls`obtain_u_set_mix3()`

and`mcmc_mix3()`

.

`dupp()`

and`mcmc_upp()`

are replaced by`dpol()`

and`mcmc_pol()`

, respectively, to facilitate a generalisation of the discrete power law, namely the Zipf-polylog distribution.`dmix()`

and`mcmc_mix()`

are replaced by`dmix2()`

and`mcmc_mix2()`

, respectively, with a new parametrisation, for the 2-component mixture distribution.`dmix3()`

and`mcmc_mix3()`

are added for the 3-component mixture distribution.

- RcppGSL is no longer needed as a LinkingTo dependency.

- The vignettes and README are updated according to the above changes.
- Also, the previous pipe operator “%>%” is replaced by the native one “|>” throughout the vignettes and README.

`get_dep()`

,`html_text_vec()`

and`get_dep_all_packages()`

now return an error message if Internet resources are not available.

The previous functionality of

`get_dep()`

is replaced by that of`get_dep_df()`

, while`get_dep_df()`

is soft deprecated. This means the former is the single function for obtaining dependencies in a non-igraph object.The argument

`type`

in`get_dep()`

and`get_graph_all_packages()`

now allows`Enhances`

and`Reverse enhances`

as the value. These two kind of dependencies are also included in the data frame obtained using`get_dep_all_packages()`

.

Examples in internal functions

`html_text_vec()`

,`get_dep_str()`

and`get_dep_vec()`

removed to minimise the errors due to no internet connection and/or timeout.Multiple dependencies are now allowed in the

`type`

argument in`get_graph_all_packages()`

.Arguments

`give_log`

in`dupp()`

&`dmix()`

changed to`log`

without changing the functionality. For uniformity,`Supp()`

&`Smix()`

are also given the additional argument`log`

.The ordering of arguments in the funcions

`*mix()`

is made consistent.

For the vignette on dependencies of all CRAN packages, community detection is added.

Replace https://cran.r-project.org/web/packages/available_packages_by_name.html by https://cran.r-project.org, in the dependency network vignette, to prevent NOTE on possibly invalid URL.

In the vignette on modelling the number of reverse dependencies, a section on fitting extreme value mixture distribution is added.

Added is a citation network of the CHI conference papers, that can serve as a comparison to the CRAN dependency network, in terms of network summaries and characteristics, such as degree distribution.

Replace https://cran.r-project.org/web/packages/available_packages_by_name.html by https://cran.r-project.org, in the manual of

`cran_dependencies`

, to prevent NOTE on possibly invalid URL.

`get_dep_all_packages()`

and`get_graph_all_packages()`

: The former is for a data frame of all dependencies of all CRAN packages, while the latter is for the graph of one type of depenedencies of all CRAN packages.`get_dep()`

replaces`get_dep_all()`

, with the same functionality.`get_dep()`

gets soft deprecated.

The argument

`type`

in`get_dep()`

and`types`

in`get_dep_df()`

allows input more flexibility. For reverse dependencies, either space or underscore is accepted for separating the words e.g.`type = "reverse suggests"`

or`type = "reverse_suggests"`

.The argument

`types`

in`get_dep_df()`

allows (as before) a character vector of dependency words. Also allowed now is`types = "all"`

which means all of the four dependencies (depends, suggests, imports, linking to) and their reverse counterparts.Previously, there were issues with string manipulation for some packages without scraping. This is because, when using

`tools::CRAN_package_db()`

, there might be no space between the package name and the left parenthesis for the version. This is not an issue if`scrape = TRUE`

as there is always a space on the CRAN page.In the output of

`get_dep_df()`

and`get_dep_all_packages()`

, any`LinkingTo`

and`Reverse linking to`

dependencies will become “linking to” (“linking_to” previously) in the variable`type`

, with “FALSE” and “TRUE” in the variable`reverse`

, respectively. This is also updated in the data`cran_dependencies`

.

The sections on obtaining dependencies of all CRAN packages is now moved to a new vignette. In this vignette, we also provide interactive visualisation of the network of

`Depends`

of all packages.The degree modelling vignette is now for

`Imports`

network, not`Depends`

network. In addition to discrete power law, a discrete extreme value mixture distribution is also used to model the same data set.

`dupp()`

and`Supp()`

: density and survival functions, respectively, of the discrete power law (above a threshold).`mcmc_upp()`

: fitting the discrete power law (above a threshold) to data using Markov chain Monte Carlo (MCMC).`dmix()`

,`Smix()`

: density and survival functions, respectively, of a discrete extreme value mixture distribution.`mcmc_mix()`

: fitting the discrete extreme value mixture distribution to data using MCMC.

- Additional argument in
`get_dep_all()`

and`get_dep_df()`

:`scrape = TRUE`

is the same as previous version, while`scrape = FALSE`

means`tools::CRAN_package_db()`

(thanks to Dirk Eddelbuettel (#1)) will be used instead. Note that changing this argument should still give the same result; the main difference is the time taken.