多元对数正态分布随机变量Rv
应该有这个属性:log(Rv)
应服从正态分布。因此,问题实际上只是生成一个多元正态分布的随机变量,并且np.exp
it.
In [1]: import numpy.random as nr
In [2]: cov = np.array([[1.0, 0.2, 0.3,],
[0.2, 1.0, 0.3,],
[0.3, 0.3, 1.0]])
In [3]: mu = np.log([0.3, 0.4, 0.5])
In [4]: mvn = nr.multivariate_normal(mu, cov, size=5)
In [5]: mvn # This is multivariate normal
Out[5]:
array([[-1.36808854, -1.32562291, -1.9706876 ],
[-2.13119289, 1.28146425, 0.66000019],
[-2.82590272, -1.22500654, -0.32635701],
[-0.4967589 , -0.34469589, -2.04084115],
[-0.85590235, -1.27133544, -0.70959595]])
In [6]: mvln = np.exp(mvn)
In [7]: mvln # This is multivariate log-normal
Out[7]:
array([[ 0.25459314, 0.26563744, 0.139361 ],
[ 0.11869562, 3.60190996, 1.9347927 ],
[ 0.05925514, 0.29375578, 0.72154754],
[ 0.60849968, 0.70843576, 0.12991938],
[ 0.42489961, 0.28045684, 0.49184289]])