WAIC Multitrace

waic_multitrace.ipynb

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   "cell_type": "code",
   "execution_count": 1,
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   "source": [
    "import numpy as np\n",
    "import pymc3 as pm"
   ]
  },
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   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
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   "source": [
    "x = np.random.normal(size=1000)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
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     "text": [
      "Auto-assigning NUTS sampler...\n",
      "Initializing NUTS using advi+adapt_diag...\n",
      "Average Loss = 1,434.5:   5%|▍         | 9687/200000 [00:00<00:13, 13954.09it/s]\n",
      "Convergence archived at 10400\n",
      "Interrupted at 10,400 [5%]: Average Loss = 1,492.5\n",
      "100%|██████████| 1000/1000 [00:00<00:00, 1514.37it/s]\n"
     ]
    }
   ],
   "source": [
    "with pm.Model() as model:\n",
    "    μ = pm.Normal('μ', 0., 10.)\n",
    "    obs = pm.Normal('obs', μ, 1., observed=x)\n",
    "    \n",
    "    trace = pm.sample(njobs=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WAIC_r(WAIC=2843.7379152678827, WAIC_se=44.677006148308983, p_WAIC=0.88625793354698179)\n",
      "WAIC_r(WAIC=2843.9272891881187, WAIC_se=44.683876069126029, p_WAIC=0.98274948575880394)\n",
      "WAIC_r(WAIC=2843.7379152678827, WAIC_se=44.677006148308983, p_WAIC=0.88625793354698179)\n"
     ]
    }
   ],
   "source": [
    "with model:\n",
    "    print(pm.waic(trace))\n",
    "    print(pm.waic(trace._straces[0]))\n",
    "    print(pm.waic(trace._straces[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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