scipy stats.gilbrat() | Python

Michael Zippo

Parameters:
- > q: onder- en bovenstaartwaarschijnlijkheid
- > x: kwantielen
- > loc: [optioneel] locatieparameter. Standaard = 0
- > schaal: [optioneel] schaalparameter. Standaard = 1
- > grootte: [tupel van ints, optioneel] vorm of willekeurige variaties.
- > momenten: [optioneel] samengesteld uit letters [`mvsk`]; `m` = gemiddelde, `v` = variantie, `s` = Fisher`s skew en `k` = Fisher`s kurtosis. (default = `mv`).
Resultaten: Gilbrat continue willekeurige variabele

Code # 1: Een continue willekeurige genereren variabele Gilbrat

Outpu t:

Distributie: [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: verschillende positionele argumenten

import matplotlib. pyplot as plt

import numpy als np

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

# Diverse positionele argumenten

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

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

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

Uitvoer:

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van scipy.stats import gilbrat

aantal = gilbrat .numargs

[] = [ 0.7 ,] * aantal

rv = gilbrat ( )

print ( " RV: " , rv)

Uitvoer:

RV: "scipy.stats._distn_infrastructure.rv_frozen object op 0x000001E39A3B4AC8 >

Code #2: Gilbrat random variabelen en kansverdeling

import numpy als np

kwantiel = np.arange ( 0,01 , 1 , 0.1 )

# Willekeurige varianten

R = gilbrat.rvs (schaal = 2 , grootte = 10 )

print ( "Willekeurige variaties:" , R)

# PDF

R = gilbrat.pdf (kwantiel, loc = 0 , schaal = 1 )

print ( "Kansverdeling: " , R)

Uitvoer:

Willekeurige variaties: [0.66090031 1.39027118 1.33876164 1.50366592 5.21419497 5.24225463 3.98547687 0.30586938 9.11346685 0.93014057] Kansverdeling: [0.00099024 0.31736749 0.5620854 0.689139 0.620854 0.64817773 2357239 0,57879516 0,52988354 0,48170703 0,43645277]

Code # 3: Grafische weergave

import numpy as np

import matplotlib.pyplot as plt

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

print ( " Distributie: " , distributie)

plot = plt.plot (distributie, rv.pdf (distributie))