CLN: Fix typos

Author: rebecca-palmer

docs/source/pitfalls.rst

@@ -108,7 +108,7 @@ relative to Poisson, that is the true model has the same dispersion as Poisson
 or is underdispersed, is inconsistent with the overdispersion assumption of
 the Negative Binomial distribution. The loglikelihood and its derivatives, as
 implemented in statsmodels, cannot be evaluated for dispersion parameter at
-zero dispersion or in a positve neighborhood of zero dispersion.
+zero dispersion or in a positive neighborhood of zero dispersion.
 
 Zero inflated models currently use either Logit or Probit as model for
 inflation. This means that no inflation is at the boundary of the parameter

statsmodels/tsa/stl/_stl.pyx

@@ -246,11 +246,11 @@ cdef class STL(object):
         self.low_pass_deg = low_pass_deg  # ildeg
         self.robust = robust
         if not _is_pos_int(low_pass_jump, False):
-            raise ValueError('low_pass_jump must be a positve integer')
+            raise ValueError('low_pass_jump must be a positive integer')
         if not _is_pos_int(seasonal_jump, False):
-            raise ValueError('seasonal_jump must be a positve integer')
+            raise ValueError('seasonal_jump must be a positive integer')
         if not _is_pos_int(trend_jump, False):
-            raise ValueError('trend_jump must be a positve integer')
+            raise ValueError('trend_jump must be a positive integer')
         self.low_pass_jump = low_pass_jump
         self.seasonal_jump = seasonal_jump
         self.trend_jump = trend_jump

statsmodels/tsa/stl/tests/test_stl.py

@@ -232,17 +232,17 @@ def test_jump_errors(default_kwargs):
     class_kwargs, _, _ = _to_class_kwargs(default_kwargs)
     endog = class_kwargs["endog"]
     period = class_kwargs["period"]
-    with pytest.raises(ValueError, match="low_pass_jump must be a positve"):
+    with pytest.raises(ValueError, match="low_pass_jump must be a positive"):
         STL(endog=endog, period=period, low_pass_jump=0)
-    with pytest.raises(ValueError, match="low_pass_jump must be a positve"):
+    with pytest.raises(ValueError, match="low_pass_jump must be a positive"):
         STL(endog=endog, period=period, low_pass_jump=1.0)
-    with pytest.raises(ValueError, match="seasonal_jump must be a positve"):
+    with pytest.raises(ValueError, match="seasonal_jump must be a positive"):
         STL(endog=endog, period=period, seasonal_jump=0)
-    with pytest.raises(ValueError, match="seasonal_jump must be a positve"):
+    with pytest.raises(ValueError, match="seasonal_jump must be a positive"):
         STL(endog=endog, period=period, seasonal_jump=1.0)
-    with pytest.raises(ValueError, match="trend_jump must be a positve"):
+    with pytest.raises(ValueError, match="trend_jump must be a positive"):
         STL(endog=endog, period=period, trend_jump=0)
-    with pytest.raises(ValueError, match="trend_jump must be a positve"):
+    with pytest.raises(ValueError, match="trend_jump must be a positive"):
         STL(endog=endog, period=period, trend_jump=1.0)