Modify the packaage to emphasize "Polya Gamma" and add URLs to papers…

… in the DESCRIPTION file.

.Rbuildignore

@@ -7,3 +7,4 @@
 ^docs$
 ^pkgdown$
 ^cran-comments\.md$
+^CRAN-SUBMISSION$

.aspell/words.pws

@@ -1,6 +1,7 @@
-personal_ws-1.1 en 5 UTF-8
+personal_ws-1.1 en 6 UTF-8
 Balamuta
 PG
-Polya-Gamma
 Polya
+Gamma
 performant
+Polson

DESCRIPTION

@@ -1,5 +1,5 @@
 Package: pg
-Title: Pólya-Gamma Distribution Sampler
+Title: Polya Gamma Distribution Sampler
 Version: 0.2.4
 Authors@R: 
     c(
@@ -10,9 +10,11 @@ Authors@R:
         email = "balamut2@illinois.edu"
       )
     )
-Description: Provides access to a high performant random distribution
-    sampler for the Pólya-Gamma Distribution using either 'C++' headers for 
-    'Rcpp' or 'RcppArmadillo' and 'R'.
+Description: Provides access to a series of highly performant random distribution
+    samplers for the Polya Gamma Distribution as described by
+    Polson, Scott, and Windle (2013) <arXiv:1205.0310> using either 'C++' headers 
+    for 'Rcpp' or 'RcppArmadillo' and 'R'. The 'C++' header approach was developed
+    to enable computations in Balamuta (2021) <https://www.ideals.illinois.edu/items/121209>.
 URL: https://tmsalab.github.io/pg/, https://github.com/tmsalab/pg
 BugReports: https://github.com/tmsalab/pg/issues
 License: GPL (>= 3)

R/RcppExports.R

@@ -1,9 +1,9 @@
 # Generated by using Rcpp::compileAttributes() -> do not edit by hand
 # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
 
-#' Sample from the Pólya-Gamma distribution PG(h, z)
+#' Sample from the Polya Gamma distribution PG(h, z)
 #'
-#' Chooses the most efficient implemented method to sample from a Pólya-Gamma
+#' Chooses the most efficient implemented method to sample from a Polya Gamma
 #' distribution. Details on algorithm selection presented below.
 #'
 #' @param n     The number of samples to taken from a PG(h, z). Used only by

R/pg_theoretical.R

@@ -1,12 +1,12 @@
-#' Theoretical Polya-Gamma Distribution's Mean and Variance
+#' Theoretical Polya Gamma Distribution's Mean and Variance
 #'
-#' Compute the theoretical mean and variance for a Polya-Gamma variable.
+#' Compute the theoretical mean and variance for a Polya Gamma variable.
 #'
 #' @param h A single `integer` value corresponding to the "shape" parameter.
 #' @param z A single `numeric` value corresponding to the "scale" parameter.
 #'
 #' @return
-#' Either the theoretical mean or theoretical variance for a Polya-Gamma
+#' Either the theoretical mean or theoretical variance for a Polya Gamma
 #' distribution.
 #'
 #' @export

README.Rmd

@@ -20,7 +20,7 @@ knitr::opts_chunk$set(
 [![Package-License](http://img.shields.io/badge/license-GPL%20(%3E=3)-brightgreen.svg?style=flat)](http://www.gnu.org/licenses/gpl-3.0.html)
 <!-- badges: end -->
 
-The goal of pg is to provide both _R_ and _C++_ header access to the Pólya-Gamma
+The goal of pg is to provide both _R_ and _C++_ header access to the Polya Gamma
 distribution sampling routine.
 
 ## Installation
@@ -35,7 +35,7 @@ devtools::install_github("tmsalab/pg")
 
 ## Usage
 
-Let `X` be a Pólya-Gamma Distribution denoted by `PG(h, z)`, where `h` is the 
+Let `X` be a Polya Gamma Distribution denoted by `PG(h, z)`, where `h` is the 
 "shape" parameter and `z` is the "scale" parameter. Presently, the following 
 sampling cases are enabled:
 
@@ -118,16 +118,16 @@ pg::rpg_vector(n, h, z)
 
 ## See also
 
-The following are useful resources regarding the Pólya-Gamma distribution.
+The following are useful resources regarding the Polya Gamma distribution.
 
 - Papers
     - "Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables" 
       by Nicholas G. Polson, James G. Scott, and Jesse Windle (2013)
-      [doi:10.1080/01621459.2013.829001](https://doi.org/10.1080/01621459.2013.829001). Paper that invented the Pólya-Gamma
-    - "Sampling Pólya-Gamma random variates: alternate and approximate techniques"
+      [doi:10.1080/01621459.2013.829001](https://doi.org/10.1080/01621459.2013.829001). Paper that invented the Polya Gamma
+    - "Sampling Polya Gamma random variates: alternate and approximate techniques"
       by Jesse Windle, Nicholas G. Polson, and James G. Scott (2014)
       <https://arxiv.org/abs/1405.0506>. Provides an efficiency overview of the
-      different sampling approaches to sampling from a Pólya-Gamma distribution.
+      different sampling approaches to sampling from a Polya Gamma distribution.
 - R Implementations:
    - [`BayesLogit`](https://cran.r-project.org/package=BayesLogit) _R_ package by
       Nicholas G. Polson, James G. Scott, and Jesse Windle. Provides the
@@ -142,7 +142,7 @@ The following are useful resources regarding the Pólya-Gamma distribution.
 - Support in other languages:
     - `Python` has the [`pypolyagamma`](https://github.com/slinderman/pypolyagamma)
       package by Scott Linderman.
-    - `Stan` [lacks an implementation](https://discourse.mc-stan.org/t/sampling-from-a-polya-gamma-distribution/8067) for the Pólya-Gamma distribution since it relies on joint proposals 
+    - `Stan` [lacks an implementation](https://discourse.mc-stan.org/t/sampling-from-a-polya-gamma-distribution/8067) for the Polya Gamma distribution since it relies on joint proposals 
     rather than full conditionals.
 
 ## Author

README.md

@@ -10,7 +10,7 @@
 <!-- badges: end -->
 
 The goal of pg is to provide both *R* and *C++* header access to the
-Pólya-Gamma distribution sampling routine.
+Polya Gamma distribution sampling routine.
 
 ## Installation
 
@@ -24,7 +24,7 @@ devtools::install_github("tmsalab/pg")
 
 ## Usage
 
-Let `X` be a Pólya-Gamma Distribution denoted by `PG(h, z)`, where `h`
+Let `X` be a Polya Gamma Distribution denoted by `PG(h, z)`, where `h`
 is the “shape” parameter and `z` is the “scale” parameter. Presently,
 the following sampling cases are enabled:
 
@@ -111,20 +111,20 @@ pg::rpg_vector(n, h, z)
 
 ## See also
 
-The following are useful resources regarding the Pólya-Gamma
+The following are useful resources regarding the Polya Gamma
 distribution.
 
 - Papers
   - “Bayesian Inference for Logistic Models Using Pólya–Gamma Latent
     Variables” by Nicholas G. Polson, James G. Scott, and Jesse
     Windle (2013)
     [doi:10.1080/01621459.2013.829001](https://doi.org/10.1080/01621459.2013.829001).
-    Paper that invented the Pólya-Gamma
-  - “Sampling Pólya-Gamma random variates: alternate and approximate
+    Paper that invented the Polya Gamma
+  - “Sampling Polya Gamma random variates: alternate and approximate
     techniques” by Jesse Windle, Nicholas G. Polson, and James G.
     Scott (2014) <https://arxiv.org/abs/1405.0506>. Provides an
     efficiency overview of the different sampling approaches to sampling
-    from a Pólya-Gamma distribution.
+    from a Polya Gamma distribution.
 - R Implementations:
   - [`BayesLogit`](https://cran.r-project.org/package=BayesLogit) *R*
     package by Nicholas G. Polson, James G. Scott, and Jesse Windle.
@@ -143,7 +143,7 @@ distribution.
     by Scott Linderman.
   - `Stan` [lacks an
     implementation](https://discourse.mc-stan.org/t/sampling-from-a-polya-gamma-distribution/8067)
-    for the Pólya-Gamma distribution since it relies on joint proposals
+    for the Polya Gamma distribution since it relies on joint proposals
     rather than full conditionals.
 
 ## Author

data-raw/custom-dictionary.R

@@ -34,9 +34,10 @@ author = c(
 )
 other = c(
   "PG",
-  "Polya-Gamma",
   "Polya",
-  "performant"
+  "Gamma",
+  "performant",
+  "Polson"
 )
 
 custom_words = c(author, other)

inst/WORDLIST

@@ -1,5 +1,6 @@
 Balamuta
 PG
-Polya-Gamma
 Polya
+Gamma
 performant
+Polson

src/rpg.cpp

@@ -1,8 +1,8 @@
 #include "pg.h"
 
-//' Sample from the Pólya-Gamma distribution PG(h, z)
+//' Sample from the Polya Gamma distribution PG(h, z)
 //'
-//' Chooses the most efficient implemented method to sample from a Pólya-Gamma
+//' Chooses the most efficient implemented method to sample from a Polya Gamma
 //' distribution. Details on algorithm selection presented below.
 //'
 //' @param n     The number of samples to taken from a PG(h, z). Used only by