From b054f4b2f502696a07099c62c33d881005624077 Mon Sep 17 00:00:00 2001
From: reshamas \n",
+ "
<xarray.Dataset>\n", - "Dimensions: (chain_draw: 8000, county: 85)\n", + "Dimensions: (chain_draw: 4000, county: 85)\n", "Coordinates:\n", " * county (county) <U17 'AITKIN' 'ANOKA' ... 'WRIGHT' 'YELLOW MEDICINE'\n", " * chain_draw (chain_draw) MultiIndex\n", - " - chain (chain_draw) int64 0 0 0 0 0 0 0 0 0 0 0 ... 3 3 3 3 3 3 3 3 3 3\n", + " - chain (chain_draw) int64 0 0 0 0 0 0 0 0 0 0 0 ... 1 1 1 1 1 1 1 1 1 1\n", " - draw (chain_draw) int64 0 1 2 3 4 5 ... 1994 1995 1996 1997 1998 1999\n", "Data variables:\n", - " mu_a (chain_draw) float64 1.403 1.438 1.447 ... 1.531 1.556 1.548\n", - " sigma_a (chain_draw) float64 0.3293 0.2812 0.2438 ... 0.3564 0.3729\n", - " mu_b (chain_draw) float64 -0.74 -0.6791 -0.5542 ... -0.7281 -0.7413\n", - " sigma_b (chain_draw) float64 0.2061 0.2563 0.3042 ... 0.1551 0.1586\n", - " a (county, chain_draw) float64 1.406 1.61 1.202 ... 1.33 1.421\n", - " b (county, chain_draw) float64 -0.6981 -1.15 ... -0.9213 -0.8833\n", - " eps (chain_draw) float64 0.7185 0.739 0.7169 ... 0.744 0.696 0.6974\n", + " mu_a (chain_draw) float64 1.451 1.565 1.442 ... 1.453 1.484 1.447\n", + " mu_b (chain_draw) float64 -0.6928 -0.7185 -0.718 ... -0.5677 -0.6226\n", + " a (county, chain_draw) float64 0.8076 1.267 1.272 ... 1.284 1.552\n", + " b (county, chain_draw) float64 -0.821 -0.5126 ... -0.5627 -0.7921\n", + " sigma_a (chain_draw) float64 0.4079 0.4258 0.2881 ... 0.4213 0.4115\n", + " sigma_b (chain_draw) float64 0.06865 0.1164 0.1179 ... 0.2244 0.1877\n", + " eps (chain_draw) float64 0.6896 0.7279 0.7023 ... 0.7221 0.7199\n", "Attributes:\n", - " created_at: 2022-01-09T13:50:31.244473\n", - " arviz_version: 0.11.4\n", + " created_at: 2022-09-29T00:38:38.322286\n", + " arviz_version: 0.12.1\n", " inference_library: pymc\n", - " inference_library_version: 4.0.0b1\n", - " sampling_time: 62.45755052566528\n", - " tuning_steps: 2000
array(['AITKIN', 'ANOKA', 'BECKER', 'BELTRAMI', 'BENTON', 'BIG STONE',\n", + " inference_library_version: 4.1.2\n", + " sampling_time: 170.9890329837799\n", + " tuning_steps: 2000
array([0.40793606, 0.42584879, 0.28811957, ..., 0.34662262, 0.42129244,\n", + " 0.41151306])
array([0.06865 , 0.1164323 , 0.11787386, ..., 0.19194422, 0.22437717,\n", + " 0.18773705])
array([0.6895734 , 0.72793761, 0.70226733, ..., 0.73061418, 0.72207634,\n", + " 0.71989122])
<xarray.Dataset>\n", "Dimensions: (obs_id: 919)\n", "Coordinates:\n", - " * obs_id (obs_id) int32 0 1 2 3 4 5 6 7 ... 911 912 913 914 915 916 917 918\n", + " * obs_id (obs_id) int64 0 1 2 3 4 5 6 7 ... 911 912 913 914 915 916 917 918\n", " floor (obs_id) float64 1.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n", "Data variables:\n", " y (obs_id) float64 0.8329 0.8329 1.099 0.09531 ... 1.629 1.335 1.099\n", "Attributes:\n", - " created_at: 2022-01-09T13:49:18.417187\n", - " arviz_version: 0.11.4\n", + " created_at: 2022-09-29T00:35:42.733760\n", + " arviz_version: 0.12.1\n", " inference_library: pymc\n", - " inference_library_version: 4.0.0b1
array([ 0, 1, 2, ..., 916, 917, 918])
array([1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n", + " inference_library_version: 4.1.2
+