Update src/neurostatslib/glm.py

Co-authored-by: William F. Broderick <[email protected]>

src/neurostatslib/glm.py

@@ -410,17 +410,12 @@ class GLMRecurrent(GLM):
 
     Parameters
     ----------
-    noise_model : nsm.NoiseModel, default=nsm.PoissonNoiseModel()
+    noise_model : 
         The noise model to use for the GLM. This defines how neural activity is generated
         based on the underlying firing rate. Common choices include Poisson and Gaussian models.
-
-    solver : slv.Solver, default=slv.RidgeSolver()
+    solver : 
         The optimization solver to use for fitting the GLM parameters.
 
-    data_type : {jnp.float32, jnp.float64}, optional
-        The numerical data type for internal calculations. If not provided, it will be inferred
-        from the data during fitting.
-
     See Also
     --------
     [GLM](../glm/#neurostatslib.glm.GLM) : Base class for the generalized linear model.