Prepare for next release

.Rbuildignore

@@ -7,7 +7,6 @@
 ^cran-comments\.md$
 ^CRAN-RELEASE$
 ^LICENSE\.md$
-^NEWS\.Rmd$
 ^README\.Rmd$
 ^data-raw$
 ^doc$
@@ -17,6 +16,5 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
 ^\.github$
-^\.covrignore$
 ^paper\.md$
 ^paper\.bib$

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: tabula
 Title: Analysis, Seriation and Visualization of Archaeological
     Count Data
-Version: 1.3.0.9000
+Version: 1.4.0
 Authors@R: 
     c(person(given = "Nicolas",
              family = "Frerebeau",

NEWS.md

@@ -1,163 +1,128 @@
+## tabula 1.4.0
 
+* Published in the [*Journal of Open Source Software*](https://doi.org/10.21105/joss.01821).
 
+### New classes and methods
+* `DiversityIndex`, `HeterogeneityIndex`, `EvennessIndex` and `RichnessIndex` S4 classes represent diversity index.
+* `index_heterogeneity()` replaces `diversity()`.
+* `index_evenness()` replaces `evenness()`.
+* `index_richness()` replaces `richness()`.
+* `index_composition()` allows to estimate asymptotic species richness.
+* `plot_diversity()` produces a diversity *vs.* sample size graph and allow to compare estimates with simulated assemblages.
+* Add replacement methods for the `*Matrix` classes.
 
+### Bugfixes & changes
+* Deprecate `diversity()`, `evenness()` and `richness()`.
 
+### Internals
+* Display progress bars only if `interactive()` is `TRUE` and {pbapply} is installed.
 
-<!-- NEWS.md is generated from NEWS.Rmd. Please edit that file -->
-
-<!-- ## tabula 1.3.0 (2019-09-20) -->
-
-## tabula 1.3.0
+## tabula 1.3.0 (release date: 2019-09-20)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3455385.svg)](https://doi.org/10.5281/zenodo.3455385)
 
 ### New classes and methods
-
-  - `Matrix` this S4 class is now the superclass of all matrix-like
-    classes.
-  - `AbundanceMatrix` this virtual S4 class is defined as the superclass
-    of `CountMatrix`, `FrequencyMatrix` and `IncidenceMatrix`.
-  - `SpaceTime` this S4 class represents space-time informations.
-  - `as_*()` coerce a `matrix` or `data.frame` to a `CountMatrix`,
-    `FrequencyMatrix`, `IncidenceMatrix`, `OccurrenceMatrix` or
-    `SimilarityMatrix`.
-  - `date_event()` replaces `dateEvent()`.
-  - `date_mcd()` allows Mean Ceramic Date estimation.
-  - `get_dates()` and `set_dates<-` allow to extract and replace
-    chronological informations in `AbundanceMatrix` objects.
-  - `plot_bertin()` and `plot_ford()` replace `plotBar()`.
-  - `plot_date()` replaces `plotDate()`.
-  - `plot_date()` gained a method for `AbundanceMatrix` objects.
-  - `plot_heatmap()` replaces `plotMatrix()`.
-  - `plot_rank()` replaces `plotRank()`.
-  - `plot_spot()` replaces `plotSpot()`.
-  - `plot_time()` produces an abundance *vs.* time graph.
-  - `refine_dates()` and `refine_seriation()` replace `refine()`.
-  - `seriate_reciprocal()` and `seriate_correspondance()` replace
-    `seriate()`.
-  - `test_diversity()` allows Shannon diversity test.
-  - `test_fit()` produces a Frequency Increment Test.
+* `Matrix` S4 class is now the superclass of all matrix-like classes.
+* `AbundanceMatrix` virtual S4 class is defined as the superclass of `CountMatrix`, `FrequencyMatrix` and `IncidenceMatrix`.
+* `SpaceTime` S4 class represents space-time informations.
+* `as_*()` coerce a `matrix` or `data.frame` to a `CountMatrix`, `FrequencyMatrix`, `IncidenceMatrix`, `OccurrenceMatrix` or `SimilarityMatrix`.
+* `date_event()` replaces `dateEvent()`.
+* `date_mcd()` allows Mean Ceramic Date estimation.
+* `get_dates()` and `set_dates<-` allow to extract and replace chronological informations in `AbundanceMatrix` objects.
+* `plot_bertin()` and `plot_ford()` replace `plotBar()`.
+* `plot_date()` replaces `plotDate()`.
+* `plot_date()` gained a method for `AbundanceMatrix` objects.
+* `plot_heatmap()` replaces `plotMatrix()`.
+* `plot_rank()` replaces `plotRank()`.
+* `plot_spot()` replaces `plotSpot()`.
+* `plot_time()` produces an abundance *vs.* time graph.
+* `refine_dates()` and `refine_seriation()` replace `refine()`.
+* `seriate_reciprocal()` and `seriate_correspondance()` replace `seriate()`.
+* `test_diversity()` allows Shannon diversity test.
+* `test_fit()` produces a Frequency Increment Test.
 
 ### Bugfixes & changes
-
-  - `CountMatrix`, `FrequencyMatrix` and `IncidenceMatrix` now also
-    contain the `SpaceTime` class.
-  - Deprecate `plotBar()`, `plotMatrix()`, `plotRank()`, `plotSpot()`,
-    `refine()`, `seriate()`.
-  - Remove `dateEvent()`.
-  - Empty rows/columns are removed prior to CA seriation to avoid error
-    in `svd()`.
+* `CountMatrix`, `FrequencyMatrix` and `IncidenceMatrix` now also contain the `SpaceTime` class.
+* Deprecate `plotBar()`, `plotMatrix()`, `plotRank()`, `plotSpot()`, `refine()`, `seriate()`.
+* Remove `dateEvent()`.
+* Empty rows/columns are removed prior to CA seriation to avoid error in `svd()`.
 
 ### Enhancements
-
-  - Add the Merzbach ceramics dataset.
-  - The `plot_date()` method for `DateModel` objects now allows to
-    display an activity or a tempo plot.
+* Add the Merzbach ceramics dataset.
+* The `plot_date()` method for `DateModel` objects now allows to display an activity or a tempo plot.
 
 ### Internals
-
-  - Reduce required R version to 3.2.
-  - Error handling has been revised and error messages have been
-    harmonized.
-  - Refer to {ggplot2} functions using `::` (stop importing the entire
-    package).
-  - Use {vdiffr} to test graphical output.
-  - Replace `FactoMinerR::CA()` with `ca::ca()` (this avoids having to
-    install all {FactoMineR} dependencies when only one function is
-    used).
-  - Remove {dplyr} from the imported packages, move {magrittr} to
-    suggested packages.
+* Reduce required R version to 3.2.
+* Error handling has been revised and error messages have been harmonized.
+* Refer to {ggplot2} functions using `::` (stop importing the entire package).
+* Use {vdiffr} to test graphical output.
+* Replace `FactoMinerR::CA()` with `ca::ca()` (this avoids having to install all {FactoMineR} dependencies when only one function is used).
+* Remove {dplyr} from the imported packages, move {magrittr} to suggested packages.
 
 ### Experimental
-
-  - When a `Matrix` object is first created, an identifier (UUID v4) is
-    generated with `generate_uuid()`. This ID is preserved when coercing
-    to another class. This makes it possible to identify objects
-    representing the same initial data and associate them with the
-    results of specific computations.
-  - `get_coordinates()` and `set_coordinates<-` allow to extract and
-    replace spatial informations in `AbundanceMatrix` objects.
-  - `get_features()` allows to convert an `AbundanceMatrix` object to a
-    `data.frame`. It is intended for compatibility with the {sf}
-    package.
+* When a `Matrix` object is first created, an identifier (UUID v4) is generated with `generate_uuid()`. This ID is preserved when coercing to another class. This makes it possible to identify objects representing the same initial data and associate them with the results of specific computations.
+* `get_coordinates()` and `set_coordinates<-` allow to extract and replace spatial informations in `AbundanceMatrix` objects.
+* `get_features()` allows to convert an `AbundanceMatrix` object to a `data.frame`. It is intended for compatibility with the {sf} package.
 
 ## tabula 1.2.0 (release date: 2019-03-20)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2600844.svg)](https://doi.org/10.5281/zenodo.2600844)
 
 ### New classes and methods
-
-  - The function `dateEvent()` allows to compute chronological models as
-    described in Bellanger and Husi (2006).
-  - `DateModel` this S4 class stores the results of `dateEvent()`.
-  - `SimilarityMatrix` this S4 class represents a (dis)similarity
-    matrix.
-  - `plotDate()` method for `DateModel` objects.
-  - `plotSpot()` methods for `SimilarityMatrix` and `OccurrenceMatrix`
-    objects.
-  - `[` operators for several classes.
+* The function `dateEvent()` allows to compute chronological models as described in Bellanger and Husi (2006).
+* `DateModel` this S4 class stores the results of `dateEvent()`.
+* `SimilarityMatrix` this S4 class represents a (dis)similarity matrix.
+* `plotDate()` method for `DateModel` objects.
+* `plotSpot()` methods for `SimilarityMatrix` and `OccurrenceMatrix` objects.
+* `[` operators for several classes.
 
 ### Bugfixes & changes
-
-  - `OccurrenceMatrix` now stores the number of times each pair of taxa
-    occurs together in at least one sample.
-  - `similarity()` now returns an object of class `SimilarityMatrix`.
-  - `plotBar()` no longer add confidence interval by default.
-  - Remove useless accessors.
+* `OccurrenceMatrix` now stores the number of times each pair of taxa occurs together in at least one sample.
+* `similarity()` now returns an object of class `SimilarityMatrix`.
+* `plotBar()` no longer add confidence interval by default.
+* Remove useless accessors.
 
 ### Enhancements
-
-  - `similarity()` gained a new estimator: binomial co-occurrence
-    assessment method (similarity between types).
-  - `seriate()` gained a new argument to pass a `BootCA` object.
+* `similarity()` gained a new estimator: binomial co-occurrence assessment method (similarity between types).
+* `seriate()` gained a new argument to pass a `BootCA` object.
 
 ### Internals
-
-  - Add an optional progress bars with {pbapply} in long running
-    functions.
+* Add an optional progress bars with {pbapply} in long running functions.
 
 ## tabula 1.1.0 (release date: 2018-12-30)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.2529084.svg)](https://doi.org/10.5281/zenodo.2529084)
 
 ### Bugfixes & changes
-
-  - `similarity()` now returns a symmetric matrix.
+* `similarity()` now returns a symmetric matrix.
 
 ### Enhancements
-
-  - `richness()` gained new estimators:
-      - For abundance data: Chao1, bias-corrected Chao1, improved Chao1
-        and Abundance-based Coverage Estimator (ACE).
-      - For replicated incidence data: Chao2, bias-corrected Chao2,
-        improved Chao2 and Incidence-based Coverage Estimator (ICE).
+* `richness()` gained new estimators:
+* For abundance data: Chao1, bias-corrected Chao1, improved Chao1 and Abundance-based Coverage Estimator (ACE).
+* For replicated incidence data: Chao2, bias-corrected Chao2, improved Chao2 and Incidence-based Coverage Estimator (ICE).
 
 ### Internals
-
-  - Add references in the `Description` field of the DESCRIPTION file.
-  - Split the documentation for alpha-diversity measures.
-  - Split the documentation for beta-diversity measures.
+* Add references in the `Description` field of the DESCRIPTION file.
+* Split the documentation for alpha-diversity measures.
+* Split the documentation for beta-diversity measures.
 
 ## tabula 1.0.0 (release date: 2018-12-03)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1881131.svg)](https://doi.org/10.5281/zenodo.1881131)
 
-  - Initial version on CRAN
+* Initial version on CRAN
 
 ### New classes and methods
-
-  - `BootCA` this S4 class stores partial bootstrap CA-based seriation
-    results.
-  - `[[` operators acting on `PermutationOrder` and `BootCA` to extract
-    parts.
+* `BootCA` this S4 class stores partial bootstrap CA-based seriation results.
+* `[[` operators acting on `PermutationOrder` and `BootCA` to extract parts.
 
 ### Bugfixes & changes
-
-  - `refine()` method for `CountMatrix` now use `stats::rmultinorm()`
-    for partial bootstrap CA.
+* `refine()` method for `CountMatrix` now use `stats::rmultinorm()` for partial bootstrap CA.
 
 ### Enhancements
-
-  - Add the Zuni and Mississippi ceramics datasets.
-  - `similarity()` gained a new estimator: the Brainerd-Robinson
-    coefficient of similarity.
+* Add the Zuni and Mississippi ceramics datasets.
+* `similarity()` gained a new estimator: the Brainerd-Robinson coefficient of similarity.
 
 ### Internals
-
-  - Add a vignette for matrix seriation.
+* Add a vignette for matrix seriation.
 
 ## tabula 0.9.0 (release date: 2018-11-16)
+[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1489945.svg)](https://doi.org/10.5281/zenodo.1489945)
 
-  - First release.
+* Beta release.