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70 | 70 | "cell_type": "code",
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71 | 71 | "execution_count": 1,
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72 | 72 | "metadata": {},
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73 |
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74 |
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75 |
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76 |
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77 |
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79 |
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80 |
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81 |
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| 73 | + "outputs": [], |
82 | 74 | "source": [
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83 | 75 | "import torch\n",
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84 | 76 | "from torch import eye, ones\n",
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276 | 268 | "cell_type": "code",
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277 | 269 | "execution_count": 9,
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278 | 270 | "metadata": {},
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279 |
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| 271 | + "outputs": [], |
309 | 272 | "source": [
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310 | 273 | "# run SBC: for each inference we draw 1000 posterior samples.\n",
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311 | 274 | "num_posterior_samples = 1_000\n",
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526 | 489 | "execution_count": 16,
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527 | 490 | "metadata": {},
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528 | 491 | "outputs": [
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556 |
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557 | 492 | {
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558 | 493 | "name": "stdout",
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559 | 494 | "output_type": "stream",
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621 | 556 | "execution_count": 18,
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622 | 557 | "metadata": {},
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623 | 558 | "outputs": [
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624 |
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652 | 559 | {
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653 | 560 | "name": "stdout",
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654 | 561 | "output_type": "stream",
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718 | 625 | "execution_count": 21,
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719 | 626 | "metadata": {},
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720 | 627 | "outputs": [
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749 | 628 | {
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750 | 629 | "name": "stdout",
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751 | 630 | "output_type": "stream",
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813 | 692 | "execution_count": 23,
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814 | 693 | "metadata": {},
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815 | 694 | "outputs": [
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816 |
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843 |
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844 | 695 | {
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845 | 696 | "name": "stdout",
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846 | 697 | "output_type": "stream",
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894 | 745 | "execution_count": 25,
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895 | 746 | "metadata": {},
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896 | 747 | "outputs": [
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924 |
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925 | 748 | {
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926 | 749 | "name": "stdout",
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927 | 750 | "output_type": "stream",
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1012 | 835 | "cell_type": "code",
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1013 | 836 | "execution_count": 27,
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1014 | 837 | "metadata": {},
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1015 |
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1016 |
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1017 |
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1029 |
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1030 |
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| 838 | + "outputs": [], |
1031 | 839 | "source": [
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1032 | 840 | "# the tarp method returns the ECP values for a given set of alpha coverage levels.\n",
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1033 | 841 | "ecp, alpha = run_tarp(\n",
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