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Abraham Flaxman aflaxman

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View 000-template.ipynb
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View 2022_01_29b_vaccine_and_infection_correlation_replication.ipynb
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View numpyro_abc_kernel.py
import numpy as np, pandas as pd, matplotlib.pyplot as plt
from collections import namedtuple
from jax import random, lax
from jax.flatten_util import ravel_pytree
import jax.numpy as jnp
import numpyro
import numpyro.distributions as dist
from numpyro.infer import MCMC, util, init_to_sample
from numpyro.infer.mcmc import MCMCKernel
View numpyro_metropolis_kernel_2.py
from collections import namedtuple
from jax import random
from jax.flatten_util import ravel_pytree
import jax.numpy as jnp
import numpyro
import numpyro.distributions as dist
from numpyro.infer import MCMC, util
from numpyro.infer.mcmc import MCMCKernel
MetState = namedtuple("MetState", ["z", "rng_key"])
View numpyro_metropolis_kernel.py
from collections import namedtuple
from jax import random
from jax.flatten_util import ravel_pytree
import jax.numpy as jnp
import numpyro
import numpyro.distributions as dist
from numpyro.infer import MCMC, util
from numpyro.infer.mcmc import MCMCKernel
MetState = namedtuple("MetState", ["z", "rng_key"]) # does it matter if it is called z or u?
View 2022_01_01a_numpyro_ab_testing_model.ipynb
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View 2021_02_12a_ergm_for_households.ipynb
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View 2020_11_12d_pymc_latent_scaled_poisson.ipynb
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View 2020_11_11a_pymc_spline_example.ipynb
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View 2020_05_07a_covid19_parametric_death_redistribution_for_nyc_discontinuity.ipynb
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