update outdated text

Author: drbenvincent

docs/source/notebooks/graded_intervention_time_series_single_channel_ols.ipynb

@@ -88,7 +88,7 @@
     "- **Computational efficiency**: Fast OLS with corrected standard errors\n",
     "- **Proven reliability**: Well-established method with strong theoretical properties\n",
     "\n",
-    "With HAC (see detailed explanation in the admonition box below):\n",
+    "With HAC (see detailed explanation in the box below):\n",
     "- ✅ **Causal estimates remain valid**: Treatment effect coefficients are unbiased\n",
     "- ✅ **Inference is corrected**: Standard errors, confidence intervals, and p-values account for autocorrelation\n",
     "- ✅ **No model specification required**: Don't need to guess AR order or lag structure\n",
@@ -147,10 +147,11 @@
    "source": [
     ":::{admonition} Implementation notes\n",
     ":class: warning\n",
-    "This notebook demonstrates the **non-Bayesian implementation** using:\n",
-    "- OLS regression first with with HAC standard errors (fast, robust inference), then with ARIMAX.\n",
-    "- Automated transform parameter estimation via grid search or continuous optimization\n",
-    "- Point estimates only (future: bootstrap confidence intervals, Bayesian uncertainty quantification)\n",
+    "This notebook demonstrates multiple approaches to Transfer Function ITS:\n",
+    "- OLS regression with HAC standard errors (fast, robust inference)\n",
+    "- OLS with ARIMAX error models (explicit autocorrelation modeling)\n",
+    "- Automated transform parameter estimation (grid search and continuous optimization)\n",
+    "- Bayesian inference with PyMC (full posterior uncertainty quantification)\n",
     ":::"
    ]
   },