0
boxcoxの機能については、私が非常に説明できないほど奇妙な再現性のある動作に遭遇しています。ログに遭遇したゼロで割るscipy.stats.boxcox
長い例えば謝罪が、具体的問題の原因このデータのようだ：
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from scipy.stats import boxcox
print(boxcox(data))
/home/swozny/untitled5/lib/python3.6/site-packages/scipy/stats/morestats.py:901: RuntimeWarning: divide by zero encountered in log
llf -= N/2.0 * np.log(np.sum((y - y_mean)**2./N, axis=0))
/home/swozny/untitled5/lib/python3.6/site-packages/scipy/optimize/optimize.py:2189: RuntimeWarning: invalid value encountered in double_scalars
w = xb - ((xb - xc) * tmp2 - (xb - xa) * tmp1)/denom
/home/swozny/untitled5/lib/python3.6/site-packages/scipy/optimize/optimize.py:1849: RuntimeWarning: invalid value encountered in double_scalars
tmp1 = (x - w) * (fx - fv)
/home/swozny/untitled5/lib/python3.6/site-packages/scipy/optimize/optimize.py:1850: RuntimeWarning: invalid value encountered in double_scalars
tmp2 = (x - v) * (fx - fw)
/home/swozny/untitled5/lib/python3.6/site-packages/scipy/optimize/optimize.py:1851: RuntimeWarning: invalid value encountered in double_scalars
p = (x - v) * tmp2 - (x - w) * tmp1
(array([ 0.12241068, 0.12241068, 0.12241068, ..., 0.12241068,
0.12241068, 0.12241068]), -8.16922204235409)
次の方法で同じ値にマッピングされているすべてのデータを見ることができるように変換：0.12241068
ただし、1つの要素を除いても、すべて正常に動作します。
print(boxcox(data[:-1]))
(array([ 7.11124803, 6.83369809, 7.15089095, ..., 6.70114334,
6.80570793, 6.59243 ]), -0.)
そして、これは私が削除任意の要素に当てはまります：
print(boxcox(data[:-2]+[data[-1]]))
(array([ 7.14427608, 6.86415735, 7.18429468, ..., 6.73041367,
6.8359141 , 7.28835118]), -0.011127011306744832)
または追加します。
print(boxcox(data[:-2]+[data[-1]]))
(array([ 28.69866725, 25.85642313, 29.12759652, ..., 23.5995206 ,
30.27105033, 0.77229995]), 0.30657228704911826)
データに問題がありますか、または機能を間違って使用していますか？