correct reference instances

Author: chiral-carbon

examples/mixture_models/dp_mix.ipynb

@@ -58,8 +58,7 @@
     "\n",
     "    $$P = \\sum_{i = 1}^\\infty \\mu_i \\delta_{\\omega_i} \\sim \\textrm{DP}(\\alpha, P_0).$$\n",
     "    \n",
-    "[Suggested Further Reading]: [A Tutorial on Dirichlet Processes\n",
-    "and Hierarchical Dirichlet Processes by Yee Whye Teh](http://mlg.eng.cam.ac.uk/tutorials/07/ywt.pdf) and {cite:p}`teh2010dirichletprocess` for a brief introduction to other flavours of Dirichlet Processes, and their applications.\n",
+    "[Suggested Further Reading]: (http://mlg.eng.cam.ac.uk/tutorials/07/ywt.pdf) and {cite:p}`teh2010dirichletprocess` for a brief introduction to other flavours of Dirichlet Processes, and their applications.\n",
     "\n",
     "We can use the stick-breaking process above to easily sample from a Dirichlet process in Python.  For this example, $\\alpha = 2$ and the base distribution is $N(0, 1)$."
    ]
@@ -949,7 +948,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The Dirichlet process mixture model is incredibly flexible in terms of the family of parametric component distributions $\\{f_{\\theta}\\ |\\ f_{\\theta} \\in \\Theta\\}$.  We illustrate this flexibility below by using Poisson component distributions to estimate the density of sunspots per year. This dataset was curated by {cite:t}`sidc2021sunspot` can be downloaded."
+    "The Dirichlet process mixture model is incredibly flexible in terms of the family of parametric component distributions $\\{f_{\\theta}\\ |\\ f_{\\theta} \\in \\Theta\\}$.  We illustrate this flexibility below by using Poisson component distributions to estimate the density of sunspots per year. This dataset was curated by {cite:t}`sidc2021sunspot` and can be downloaded."
    ]
   },
   {