diff --git a/EpiAware/src/EpiObsModels/ObservationErrorModels/AbstractTuringObservationModel.jl b/EpiAware/src/EpiObsModels/ObservationErrorModels/AbstractTuringObservationModel.jl
index b068b01bd..89a7d208a 100644
--- a/EpiAware/src/EpiObsModels/ObservationErrorModels/AbstractTuringObservationModel.jl
+++ b/EpiAware/src/EpiObsModels/ObservationErrorModels/AbstractTuringObservationModel.jl
@@ -33,7 +33,7 @@ Generates priors for the observation error model. This should return a named tup
 end
 
 @doc raw"
-Generates the observation error distribution for the observation error model. This function should return the distribution for the observation error given the expected observation value `Y_t` and the priors generated by `generate_observation_error_priors`.
+The observation error distribution for the observation error model. This function should return the distribution for the observation error given the expected observation value `Y_t` and the priors generated by `generate_observation_error_priors`.
 "
 function observation_error(obs_model::AbstractTuringObservationErrorModel, Y_t)
     @info "No concrete implementation for `observation_error` is defined."
diff --git a/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl b/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl
index a041e9c07..f4eeaeb3a 100644
--- a/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl
+++ b/EpiAware/src/EpiObsModels/ObservationErrorModels/NegativeBinomialError.jl
@@ -35,6 +35,9 @@ struct NegativeBinomialError{S <: Sampleable, T <: AbstractFloat} <:
     end
 end
 
+@doc raw"
+Generates observation error priors based on the `NegativeBinomialError` observation model. This function generates the cluster factor prior for the negative binomial error model.
+"
 @model function generate_observation_error_priors(
         obs_model::NegativeBinomialError, Y_t, y_t)
     cluster_factor ~ obs_model.cluster_factor_prior
@@ -42,6 +45,9 @@ end
     return (; sq_cluster_factor)
 end
 
+@doc raw"
+This function generates the observation error model based on the negative binomial error model with a positive shift. It dispatches to the `NegativeBinomialMeanClust` distribution.
+"
 function observation_error(obs_model::NegativeBinomialError, Y_t, sq_cluster_factor)
     return NegativeBinomialMeanClust(Y_t + obs_model.pos_shift,
         sq_cluster_factor)
diff --git a/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl b/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl
index 600d86a07..cea48fffd 100644
--- a/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl
+++ b/EpiAware/src/EpiObsModels/ObservationErrorModels/PoissonError.jl
@@ -1,7 +1,6 @@
 @doc raw"
 The `PoissonError` struct represents an observation model for Poisson errors. It
-is a subtype of `AbstractTuringObservationErrorModel`. Note that
-when Y_t is shorter than y_t, then the first `length(y_t) - length(Y_t)` elements of y_t are assumed to be missing.
+is a subtype of `AbstractTuringObservationErrorModel`.
 
 ## Constructors
 - `PoissonError(; pos_shift::AbstractFloat = 0.)`: Constructs a `PoissonError`
@@ -25,6 +24,10 @@ struct PoissonError{T <: AbstractFloat} <: AbstractTuringObservationErrorModel
     end
 end
 
+@doc raw"
+The observation error model for Poisson errors. This function generates the
+observation error model based on the Poisson error model with a positive shift.
+"
 function observation_error(obs_model::PoissonError, Y_t)
     return Poisson(Y_t + obs_model.pos_shift)
 end