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    "# Lecture Notes By Topic\n",
    "\n",
    "These notes are intended for my students and are a synthesis of numerous sources including:\n",
    "* Bayesian Data Analyis, 3rd Edition (Gelmen et al.)\n",
    "* Conteporary Bayesian Econometrics and Statistics (Geweke)\n",
    "* Series of blog posts \n",
    "    * Thomas Wiecke (http://twiecki.github.io/)\n",
    "    * Jake Vanderplas (https://jakevdp.github.io/)\n",
    "* Selected lecture notes by Patrick Lam (http://www.patricklam.org/)\n",
    "\n",
    "Of course, all errors are my own.\n",
    "    \n",
    "\n",
    "## Preliminaries and Review\n",
    "\n",
    "Please install Anaconda Python [following these instructions.](\n",
    "./bayesian_install_python.html)\n",
    "\n",
    "1. [Maximum Likelihood](./econ_407_notes_mle.html) (from ECON407).\n",
    "2. [Python Numpy Linear Algebra](./bayesian_lin_alg.html)\n",
    "3. Python [Pandas Basics](./bayesian_pandas.html)\n",
    "4. Python [Statistical Functions in Scipy Basics](./bayesian_stats.html).\n",
    "\n",
    "## Bayesian Statistics and Python\n",
    "\n",
    "1. [Sampling Methods and Frequentist Statistics](./bayesian_1.html)\n",
    "2. [Introduction to Bayesian Statistics](./bayesian_2.html)\n",
    "3. [Bayes Rule and Monte Carlo Markov Chains](./bayesian_3.html)\n",
    "4. [Properties of MCMC](./bayesian_4.html)\n",
    "5. [Convergence Diagnostics](./bayesian_5.html)\n",
    "6. [Inference](./bayesian_6.html)\n",
    "7. [Introduction to PyMC3](./bayesian_7.html)\n",
    "8. [Sampling Methods](./bayesian_8.html)\n",
    "\n",
    "## Some Models\n",
    "\n",
    "1. Heirarchical Models\n",
    "2. Multinomial Probit\n",
    "3. Time Series Applications\n",
    "4. Switching Models \n",
    "5. Time Series Models"
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