typos

Author: bgctw

src/DoubleMM/f_doubleMM.jl

@@ -280,8 +280,8 @@ function HVI.gen_hybridproblem_synthetic(rng::AbstractRNG, prob::DoubleMMCase;
     θMs_true = int_θMs_sites(scale_centered_at(θMs_true0, θM, FloatType(0.1)))
     f = get_hybridproblem_PBmodel(prob; scenario, gdev = identity, use_all_sites = true)
     #xP = fill((; S1 = xP_S1, S2 = xP_S2), n_site)
-    int_xPn = ComponentArrayInterpreter(int_xP1, (n_site,))
-    xP = int_xPn(vcat(repeat(xP_S1, 1, n_site), repeat(xP_S2, 1, n_site)))
+    int_xP_sites = ComponentArrayInterpreter(int_xP1, (n_site,))
+    xP = int_xP_sites(vcat(repeat(xP_S1, 1, n_site), repeat(xP_S2, 1, n_site)))
     #xP[:S1,:]
     θP = par_templates.θP
     #θint = ComponentArrayInterpreter( (size(θMs_true,2),), CA.getaxes(vcat(θP, θMs_true[:,1])))

src/elbo.jl

@@ -164,7 +164,7 @@ Returns an NamedTuple `(; y, θsP, θsMs, entropy_ζ)` with entries
   that are kept constant across sites.
 - `θsMs`: ComponentArray `(n_site, n_θM, n_sample_pred)` of PBM model parameters
   that vary by site.
-- `entropy_ζ`: The entroy of the log-determinant of the transformation of 
+- `entropy_ζ`: The entropy of the log-determinant of the transformation of 
   the set of model parameters, which is involved in uncertainty quantification.
 """
 function predict_hvi(rng, prob::AbstractHybridProblem; scenario, kwargs...)