scipy.stats python
from scipy.stats import beta >>> import matplotlib.pyplot as plt >>> fig, ... a, b = 2.31, 0.627 >>> mean, var, skew, kurt = beta.stats(a, b, moments='mvsk'). ,In this tutorial we discuss many, but certainly not all, features of scipy.stats . ,An overview of statistical functions is given below. Several of these functions have a similar version in scipy.stats.mstats which work for masked arrays. ,from scipy.stats import uniform >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(1, 1) ... mean, var, skew, kurt = uniform.stats(moments='mvsk'). ,scipy.stats. norm = <scipy.stats._continuous_distns.norm_gen object>[source]¶. A normal continuous random variable. The location ( loc ) keyword specifies the ... ,from scipy.stats import t >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(1, 1) ... df = 2.74 >>> mean, var, skew, kurt = t.stats(df, moments='mvsk'). , In the code samples below we assume that the scipy.stats ...,from scipy.stats import norm >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(1, 1). Calculate a few first moments: >>> >>> mean, var, skew, kurt ... , Statistical functions for masked arrays (scipy.stats.mstats).,from scipy.stats import poisson >>> import matplotlib.pyplot as plt >>> fig, ... mu = 0.6 >>> mean, var, skew, kurt = poisson.stats(mu, moments='mvsk').
| 相關軟體 Python 資訊 | |
|---|---|
 scipy.stats python 相關參考資料
scipy.stats.beta — SciPy v1.2.1 Reference Guide - SciPy.org
from scipy.stats import beta >>> import matplotlib.pyplot as plt >>> fig, ... a, b = 2.31, 0.627 >>> mean, var, skew, kurt = beta.stats(a, b, moments='mvsk'). https://docs.scipy.org Statistics (scipy.stats) — SciPy v1.2.1 Reference Guide
In this tutorial we discuss many, but certainly not all, features of scipy.stats . https://docs.scipy.org Statistical functions (scipy.stats) — SciPy v1.2.1 Reference Guide
An overview of statistical functions is given below. Several of these functions have a similar version in scipy.stats.mstats which work for masked arrays. https://docs.scipy.org scipy.stats.uniform — SciPy v1.2.1 Reference Guide - SciPy.org
from scipy.stats import uniform >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(1, 1) ... mean, var, skew, kurt = uniform.stats(moments='mvsk'). https://docs.scipy.org scipy.stats.norm — SciPy v1.2.1 Reference Guide - SciPy.org
scipy.stats. norm = <scipy.stats._continuous_distns.norm_gen object>[source]¶. A normal continuous random variable. The location ( loc ) keyword specifies the ... https://docs.scipy.org scipy.stats.t — SciPy v1.2.1 Reference Guide - SciPy.org
from scipy.stats import t >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(1, 1) ... df = 2.74 >>> mean, var, skew, kurt = t.stats(df, moments='mvsk').... https://docs.scipy.org Statistics (scipy.stats) — SciPy v1.0.0 Reference Guide
In the code samples below we assume that the scipy.stats ... https://docs.scipy.org scipy.stats.norm — SciPy v0.16.1 Reference Guide
from scipy.stats import norm >>> import matplotlib.pyplot as plt >>> fig, ax = plt.subplots(1, 1). Calculate a few first moments: >>> >>> mean, var, skew, kurt ... https://docs.scipy.org Statistical functions (scipy.stats) — SciPy v0.15.1 Reference Guide
Statistical functions for masked arrays (scipy.stats.mstats). https://docs.scipy.org scipy.stats.poisson — SciPy v1.2.1 Reference Guide - SciPy.org
from scipy.stats import poisson >>> import matplotlib.pyplot as plt >>> fig, ... mu = 0.6 >>> mean, var, skew, kurt = poisson.stats(mu, moments='mvsk'). https://docs.scipy.org |