latest comment fixes from 10/25

flatironinstitute · Oct 26, 2024 · b0fcfe4 · b0fcfe4
1 parent 71cfe4c
commit b0fcfe4
Showing 1 changed file with 6 additions and 3 deletions.
diff --git a/src/nemos/glm.py b/src/nemos/glm.py
@@ -108,7 +108,7 @@ class GLM(BaseRegressor):
     --------
     >>> import nemos as nmo
 
-    >>> # define simple GLM model
+    >>> # define single neuron GLM model
     >>> model = nmo.glm.GLM()
     >>> print("Regularizer type: ", type(model.regularizer))
     Regularizer type:  <class 'nemos.regularizer.UnRegularized'>
@@ -330,7 +330,7 @@ def predict(self, X: DESIGN_INPUT_TYPE) -> jnp.ndarray:
         --------
         >>> # example input
         >>> import numpy as np
-        >>> X, y = np.random.normal(size=(10, 2)), np.random.uniform(size=10)
+        >>> X, y = np.random.normal(size=(10, 2)), np.random.poisson(size=10)
 
         >>> # define and fit a GLM
         >>> import nemos as nmo
@@ -445,7 +445,7 @@ def score(
         --------
         >>> # example input
         >>> import numpy as np
-        >>> X, y = np.random.normal(size=(10, 2)), np.random.uniform(size=10)
+        >>> X, y = np.random.normal(size=(10, 2)), np.random.poisson(size=10)  
 
         >>> import nemos as nmo
         >>> model = nmo.glm.GLM()
@@ -454,6 +454,9 @@ def score(
         >>> # get model score
         >>> log_likelihood_score = model.score(X, y)
 
+        >>> # get a pseudo-R2 score  
+        >>> pseudo_r2_score = model.score(X, y, score_type='pseudo-r2-McFadden')
+
         Notes
         -----
         The log-likelihood is not on a standard scale, its value is influenced by many factors,