update links using {ref}

Author: pradyutf

examples/survival_analysis/weibull_aft.ipynb

@@ -57,7 +57,7 @@
    "source": [
     "## Dataset\n",
     "\n",
-    "The {ref}`bayes_param_survival_pymc3` notebook introduced two different accelerated failure time (AFT) models: Weibull and log-linear. In this notebook, we present three different parameterizations of the Weibull AFT model.\n",
+    "The {ref}`previous example notebook on Bayesian parametric survival analysis <bayes_param_survival_pymc3>` introduced two different accelerated failure time (AFT) models: Weibull and log-linear. In this notebook, we present three different parameterizations of the Weibull AFT model.\n",
     "\n",
     "The data set we'll use is the `flchain` R data set, which comes from a medical study investigating the effect of serum free light chain (FLC) on lifespan. Read the full documentation of the data by running:\n",
     "\n",

examples/survival_analysis/weibull_aft.myst.md

@@ -39,7 +39,7 @@ az.style.use("arviz-darkgrid")
 
 ## Dataset
 
-The {ref}`bayes_param_survival_pymc3` notebook introduced two different accelerated failure time (AFT) models: Weibull and log-linear. In this notebook, we present three different parameterizations of the Weibull AFT model.
+The {ref}`previous example notebook on Bayesian parametric survival analysis <bayes_param_survival_pymc3>` introduced two different accelerated failure time (AFT) models: Weibull and log-linear. In this notebook, we present three different parameterizations of the Weibull AFT model.
 
 The data set we'll use is the `flchain` R data set, which comes from a medical study investigating the effect of serum free light chain (FLC) on lifespan. Read the full documentation of the data by running: