diff --git a/dynamax/linear_gaussian_ssm/models.py b/dynamax/linear_gaussian_ssm/models.py
index 7b05c788..f5b5f019 100644
--- a/dynamax/linear_gaussian_ssm/models.py
+++ b/dynamax/linear_gaussian_ssm/models.py
@@ -191,21 +191,21 @@ def emission_distribution(
         self,
         params: ParamsLGSSM,
         state: Float[Array, " state_dim"],
-        inputs: Optional[Float[Array, "ntime input_dim"]]=None
+        inputs: Optional[Float[Array, "ntime input_dim"]] = None
     ) -> tfd.Distribution:
         inputs = inputs if inputs is not None else jnp.zeros(self.input_dim)
         mean = params.emissions.weights @ state + params.emissions.input_weights @ inputs
         if self.has_emissions_bias:
             mean += params.emissions.bias
         return MVN(mean, params.emissions.cov)
-    
+
     def sample(
         self,
         params: ParamsLGSSM,
         key: PRNGKey,
         num_timesteps: int,
-        inputs: Optional[Float[Array, "ntime input_dim"]] = None
-    ) -> PosteriorGSSMFiltered:
+        inputs: Optional[Float[Array, "ntime input_dim"]] = None,
+    ) -> Tuple[Float[Array, "num_timesteps state_dim"], Float[Array, "num_timesteps emission_dim"]]:
         return lgssm_joint_sample(params, key, num_timesteps, inputs)
 
     def marginal_log_prob(