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我正在探索在 pymc 中使用有界分布。我试图在两个值之间绑定 Gamma 先验分布。由于缺少测试值，模型规范似乎失败了。我怎样才能传递一个 testval 参数，以便我能够指定这些类型的模型？

为了完整起见，我已经包含了错误，以及下面的一个最小示例。谢谢！

AttributeError: <pymc.quickclass.Gamma object at 0x110a62890> has no default value to use, checked for: ['median', 'mean', 'mode'] pass testval argument or provide one of these. 

import pymc as pm
import numpy as np

ndims = 2
nobs = 20

zdata = np.random.normal(loc=0, scale=0.75, size=(ndims, nobs))

BoundedGamma = pm.Bound(pm.Gamma, 0.5, 2)

with pm.Model() as model:
    xbound = BoundedGamma('xbound', alpha=1, beta=2)
    z = pm.Normal('z', mu=0, tau=xbound, shape=(ndims, 1), observed=zdata)

编辑：出于参考目的，这是一个利用有界伽马先验分布的简单工作模型：

import pymc as pm
import numpy as np

ndims = 2
nobs = 20

zdata = np.random.normal(loc=0, scale=0.75, size=(ndims, nobs))

BoundedGamma = pm.Bound(pm.Gamma, 0.5, 2)

with pm.Model() as model:
    xbound = BoundedGamma('xbound', alpha=1, beta=2, testval=2)
    z = pm.Normal('z', mu=0, tau=xbound, shape=(ndims, 1), observed=zdata)

with model:
    start = pm.find_MAP()

with model:
    step = pm.NUTS()

with model: 
    trace = pm.sample(3000, step, start)

pm.traceplot(trace);
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1 回答 1

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使用该行：

xbound = BoundedGamma('xbound', alpha=1, beta=2, testval=1)
于 2013-11-08T21:31:53.353 回答