diff --git a/examples/controlled.jl b/examples/controlled.jl
index 1f2451b9..764d3939 100644
--- a/examples/controlled.jl
+++ b/examples/controlled.jl
@@ -66,7 +66,7 @@ Simulation requires a vector of controls, each being a vector itself with the ri
 Let us build several sequences of variable lengths.
 =#
 
-control_seqs = [[randn(rng, d) for t in 1:rand(100:200)] for k in 1:100];
+control_seqs = [[randn(rng, d) for t in 1:rand(100:200)] for k in 1:300];
 obs_seqs = [rand(rng, hmm, control_seq).obs_seq for control_seq in control_seqs];
 
 obs_seq = reduce(vcat, obs_seqs)
@@ -151,5 +151,5 @@ hcat(hmm_est.dist_coeffs[2], hmm.dist_coeffs[2])
 
 @test hmm_est.dist_coeffs[1] ≈ hmm.dist_coeffs[1] atol = 0.05  #src
 @test hmm_est.dist_coeffs[2] ≈ hmm.dist_coeffs[2] atol = 0.05  #src
-test_coherent_algorithms(rng, hmm, control_seq; seq_ends, hmm_guess, atol=0.08, init=false)  #src
+test_coherent_algorithms(rng, hmm, control_seq; seq_ends, hmm_guess, init=false)  #src
 test_type_stability(rng, hmm, control_seq; seq_ends, hmm_guess)  #src
diff --git a/examples/temporal.jl b/examples/temporal.jl
index 9c9549f4..2c59277b 100644
--- a/examples/temporal.jl
+++ b/examples/temporal.jl
@@ -76,7 +76,7 @@ obs_seq'
 We now generate several sequences of variable lengths, for inference and learning tasks.
 =#
 
-control_seqs = [1:rand(rng, 100:200) for k in 1:1000]
+control_seqs = [1:rand(rng, 300:500) for k in 1:1000]
 obs_seqs = [rand(rng, hmm, control_seqs[k]).obs_seq for k in eachindex(control_seqs)];
 
 obs_seq = reduce(vcat, obs_seqs)
@@ -184,5 +184,5 @@ map(mean, hcat(obs_distributions(hmm_est, 2), obs_distributions(hmm, 2)))
 # ## Tests  #src
 
 @test mean(obs_seq[1:2:end]) < 0 < mean(obs_seq[2:2:end])  #src
-test_coherent_algorithms(rng, hmm, control_seq; seq_ends, hmm_guess, atol=0.09, init=false)  #src
+test_coherent_algorithms(rng, hmm, control_seq; seq_ends, hmm_guess, init=false)  #src
 test_type_stability(rng, hmm, control_seq; seq_ends, hmm_guess)  #src
diff --git a/examples/types.jl b/examples/types.jl
index 628155c7..32901c46 100644
--- a/examples/types.jl
+++ b/examples/types.jl
@@ -158,7 +158,7 @@ Another useful array type is [StaticArrays.jl](https://github.com/JuliaArrays/St
 
 seq_ends = cumsum(rand(rng, 100:200, 1000));  #src
 control_seq = fill(nothing, last(seq_ends));  #src
-test_coherent_algorithms(rng, hmm, control_seq; seq_ends, hmm_guess, init=false, atol=0.08)  #src
+test_coherent_algorithms(rng, hmm, control_seq; seq_ends, hmm_guess, init=false)  #src
 test_type_stability(rng, hmm, control_seq; seq_ends, hmm_guess)  #src
 # https://github.com/JuliaSparse/SparseArrays.jl/issues/469  #src
 @test_skip test_allocations(rng, hmm, control_seq; seq_ends, hmm_guess)  #src
diff --git a/test/correctness.jl b/test/correctness.jl
index 7b2706d1..d495f460 100644
--- a/test/correctness.jl
+++ b/test/correctness.jl
@@ -13,7 +13,7 @@ rng = StableRNG(63)
 
 ## Settings
 
-T, K = 50, 200
+T, K = 100, 200
 
 init = [0.4, 0.6]
 init_guess = [0.5, 0.5]