scipy stats.halfcauchy () | python

NumPy | Python Methods and Functions

scipy.stats.halfcauchy () is a continuous Half-Cauchy random variable that is defined in a standard format and with some shape parameters to complete its specification.

Parameters:
- & gt; q: lower and upper tail probability
- & gt; x: quantiles
- & gt; loc: [optional] location parameter. Default = 0
- & gt; scale: [optional] scale parameter. Default = 1
- & gt; size: [tuple of ints, optional] shape or random variates.
- & gt; moments: [optional] composed of letters [`mvsk`]; `m` = mean, `v` = variance, `s` = Fisher`s skew and `k` = Fisher`s kurtosis. (default = `mv`).

Results: Half-Cauchy continuous random variable

Code # 1: Create continuous random variable random variable with half Cauchy

from scipy.stats import halfcauchy

numargs = halfcauchy.numargs

[] = [ 0.7 ,] * numargs
rv = halfcauchy)
< code class = "functions"> print ( "RV:" , rv)

Output:
RV: & lt; scipy.stats._distn_infrastructure.rv_frozen object at 0x000001E39A272470 & gt;

Code # 2: semi-cats of random variables and probability distribution

import numpy as np

quantile = np.arange ( 0.01 , 1 , 0.1 )

# Random Variants

R = halfcauchy.rvs (scale = 2 , size = 10 )

print ( "Random Variates:" , R)
# PDF
R = halfcauchy.pdf (quantile, loc = 0 , scale = 1 ) print ( "Probability Distribution:" , R)

Output:

Random Variates: [6.99019514 4.03402743 6.59099197 2.54849344 5.22950683 0.02399243 0.43431935 2.38057697 8.43432847 10.53182273] Probability Distribution: [ 0.63655612 0.62900877 0.60973065 0.58080446 0.54500451 0.50521369 0.46397476 0.42325628 0.38440902 0.34824122]

Code # 3: Graphic representation.

import numpy as np

import matplotlib.pyplot as plt

distribution = np.linspace ( 0 , np.minimum (rv.dist.b, 3 ))

print ( "Distribution:" , distribution)
plot = plt.plot (distribution, rv.pdf (distributi on))

Output:

Distribution: [0. 0.06122449 0.12244898 0.18367347 0.24489796 0.30612245 0.36734694 0.42857143 0.48979592 0.55102041 0.6122449 0.67346939 0.73469388 0.79591837 0.85714286 0.91836735 0.97959184 1.04081633 1.10204082 1.16326531 1.2244898 1.28571429 1.34693878 1.40816327 1.46938776 1.53061224 1.59183673 1.65306122 1.71428571 1.7755102 1.83673469 1.89795918 1.95918367 2.02040816 2.08163265 2.14285714 2.20408163 2.26530612 2.32653061 2.3877551 2.44897959 2.51020408 2.57142857 2.63265306 2.69387755 2.75510204 2.81632653 2.87755102 2.93877551 3. ]

Code # 4: Various Positional Arguments

import matplotlib. pyplot as plt

import numpy as np

x = np.linspace ( 0 , 5 , 100 )

# Various positional arguments

y1 = halfcauchy .pdf (x, 1 , 3 )

y2 = halfcauchy .pdf ( x, 1 , 4 )

plt.plot (x, y1, "*" , x, y2, "r--" )

Output:

scipy stats.halfcauchy () | python

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