diff --git a/examples/types.jl b/examples/types.jl
index d4966a5f..0945be63 100644
--- a/examples/types.jl
+++ b/examples/types.jl
@@ -154,7 +154,7 @@ Another useful array type is [StaticArrays.jl](https://github.com/JuliaArrays/St
 
 # ## Tests  #src
 
-@test_broken nnz(log_transition_matrix(hmm)) == nnz(transition_matrix(hmm))  #src
+@test nnz(log_transition_matrix(hmm)) == nnz(transition_matrix(hmm))  #src
 
 seq_ends = cumsum(rand(rng, 100:200, 100));  #src
 control_seq = fill(nothing, last(seq_ends));  #src
diff --git a/src/inference/viterbi.jl b/src/inference/viterbi.jl
index abf254e8..09e18a26 100644
--- a/src/inference/viterbi.jl
+++ b/src/inference/viterbi.jl
@@ -62,7 +62,7 @@ function viterbi!(
         logtrans = log_transition_matrix(hmm, control_seq[t - 1])
         ϕₜ, ϕₜ₋₁ = view(ϕ, :, t), view(ϕ, :, t - 1)
         ψₜ = view(ψ, :, t)
-        argmaxplus_mul!(ϕₜ, ψₜ, transpose(logtrans), ϕₜ₋₁)
+        argmaxplus_transmul!(ϕₜ, ψₜ, logtrans, ϕₜ₋₁)
         ϕₜ .+= logBₜ
     end
 
diff --git a/src/types/hmm.jl b/src/types/hmm.jl
index 476eaeae..a9310798 100644
--- a/src/types/hmm.jl
+++ b/src/types/hmm.jl
@@ -79,7 +79,7 @@ function StatsAPI.fit!(
     end
     # Update logs
     hmm.loginit .= log.(hmm.init)
-    hmm.logtrans .= log.(hmm.trans)
+    mynonzeros(hmm.logtrans) .= log.(mynonzeros(hmm.trans))
     # Safety check
     @argcheck valid_hmm(hmm)
     return nothing
diff --git a/src/utils/linalg.jl b/src/utils/linalg.jl
index 07f8f31a..506b29e4 100644
--- a/src/utils/linalg.jl
+++ b/src/utils/linalg.jl
@@ -7,6 +7,10 @@ mynnz(x::AbstractArray) = length(mynonzeros(x))
 
 elementwise_log(x::AbstractArray) = log.(x)
 
+function elementwise_log(A::SparseMatrixCSC)
+    return SparseMatrixCSC(A.m, A.n, A.colptr, A.rowval, log.(A.nzval))
+end
+
 """
     mul_rows_cols!(B, l, A, r)
 
@@ -40,26 +44,51 @@ function mul_rows_cols!(
 end
 
 """
-    argmaxplus_mul!(y, ind, A, x)
+    argmaxplus_transmul!(y, ind, A, x)
 
-Perform the in-place multiplication `A * x` _in the sense of max-plus algebra_, store the result in `y`, and store the index of the maximum for each row in `ind`.
+Perform the in-place multiplication `transpose(A) * x` _in the sense of max-plus algebra_, store the result in `y`, and store the index of the maximum for each component of `y` in `ind`.
 """
-function argmaxplus_mul!(
+function argmaxplus_transmul!(
     y::AbstractVector{R},
     ind::AbstractVector{<:Integer},
     A::AbstractMatrix,
     x::AbstractVector,
 ) where {R}
-    @argcheck axes(A, 1) == eachindex(y)
-    @argcheck axes(A, 2) == eachindex(x)
+    @argcheck axes(A, 1) == eachindex(x)
+    @argcheck axes(A, 2) == eachindex(y)
     y .= typemin(R)
     ind .= 0
     for j in axes(A, 2)
         for i in axes(A, 1)
-            z = A[i, j] + x[j]
-            if z > y[i]
-                y[i] = z
-                ind[i] = j
+            z = A[i, j] + x[i]
+            if z > y[j]
+                y[j] = z
+                ind[j] = i
+            end
+        end
+    end
+    return y
+end
+
+function argmaxplus_transmul!(
+    y::AbstractVector{R},
+    ind::AbstractVector{<:Integer},
+    A::SparseMatrixCSC,
+    x::AbstractVector,
+) where {R}
+    @argcheck axes(A, 1) == eachindex(x)
+    @argcheck axes(A, 2) == eachindex(y)
+    Anz = nonzeros(A)
+    Arv = rowvals(A)
+    y .= typemin(R)
+    ind .= 0
+    for j in axes(A, 2)
+        for k in nzrange(A, j)
+            i = Arv[k]
+            z = Anz[k] + x[i]
+            if z > y[j]
+                y[j] = z
+                ind[j] = i
             end
         end
     end