diff --git a/DESCRIPTION b/DESCRIPTION
index a1a0df7..516b806 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -4,9 +4,10 @@ Title: Distributions for Ecological Models in 'nimble'
 Version: 0.5.0
 Maintainer: Benjamin R. Goldstein <ben.goldstein@berkeley.edu>
 Authors@R: c(person("Benjamin R.", "Goldstein", role = c("aut", "cre"),
-                     email = "ben.goldstein@berkeley.edu"),
+                     email = "bgoldst2@ncsu.edu"),
               person("Daniel", "Turek", role = "aut"),
               person("Lauren", "Ponisio", role = "aut"),
+              person("Wei", "Zhang", role = "ctb"),
               person("Perry", "de Valpine", role = "aut"))
 Date: 2024-06-24
 Description: Common ecological distributions for 'nimble' models in the form of nimbleFunction objects. 
diff --git a/R/dNmixture.R b/R/dNmixture.R
index 22726aa..4edaa23 100644
--- a/R/dNmixture.R
+++ b/R/dNmixture.R
@@ -2,7 +2,9 @@
 #'
 #' \code{dNmixture_s} and \code{dNmixture_v} provide Poisson-Binomial mixture
 #' distributions of abundance ("N-mixture") for use in \code{nimble} models.
-#' Overdispersion alternatives are also provided .
+#' Overdispersion alternatives using the negative binomial distribution (for
+#' the abundance submodel) and the beta binomial distribution (for the detection
+#' submodel) are also provided.
 #'
 #' @name dNmixture
 #'
@@ -80,8 +82,8 @@
 #' Beta-binomial-Poisson: BBP N-mixture uses a beta binomial distribution for
 #' detection probabilities and a Poisson distribution for abundance. The beta
 #' binomial distribution has scalar overdispersion parameter s (0-Inf). We
-#' parameterize such that the variance of the beta binomial is \code{N \* prob
-#' \* (1-prob) \* (N + s) / (s + 1)}, with greater s indicating less variance
+#' parameterize such that the variance of the beta binomial is \code{N * prob
+#' * (1-prob) * (N + s) / (s + 1)}, with greater s indicating less variance
 #' (greater-than-binomial relatedness between observations at the site) and s ->
 #' 0 indicating the binomial. The BBP is available in three suffixed forms:
 #' \code{dNmixture_BBP_v} is used if \code{prob} varies between observations,
diff --git a/man/dNmixture.Rd b/man/dNmixture.Rd
index 44d6e96..76c5966 100644
--- a/man/dNmixture.Rd
+++ b/man/dNmixture.Rd
@@ -112,7 +112,9 @@ For \code{rNmixture_s} and \code{rNmixture_v}: a simulated detection history, \c
 \description{
 \code{dNmixture_s} and \code{dNmixture_v} provide Poisson-Binomial mixture
 distributions of abundance ("N-mixture") for use in \code{nimble} models.
-Overdispersion alternatives are also provided .
+Overdispersion alternatives using the negative binomial distribution (for
+the abundance submodel) and the beta binomial distribution (for the detection
+submodel) are also provided.
 }
 \details{
 These nimbleFunctions provide distributions that can be
@@ -157,8 +159,8 @@ the site (so both x and prob are scalar).
 Beta-binomial-Poisson: BBP N-mixture uses a beta binomial distribution for
 detection probabilities and a Poisson distribution for abundance. The beta
 binomial distribution has scalar overdispersion parameter s (0-Inf). We
-parameterize such that the variance of the beta binomial is \code{N \* prob
-\* (1-prob) \* (N + s) / (s + 1)}, with greater s indicating less variance
+parameterize such that the variance of the beta binomial is \code{N * prob
+* (1-prob) * (N + s) / (s + 1)}, with greater s indicating less variance
 (greater-than-binomial relatedness between observations at the site) and s ->
 0 indicating the binomial. The BBP is available in three suffixed forms:
 \code{dNmixture_BBP_v} is used if \code{prob} varies between observations,