Python - Levy_stable Distribution in Statistics Last Updated : 10 Jan, 2020 Comments Improve Suggest changes Like Article Like Report scipy.stats.levy_stable() is a Levy-stable continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x : quantiles loc : [optional]location parameter. Default = 0 scale : [optional]scale parameter. Default = 1 size : [tuple of ints, optional] shape or random variates. moments : [optional] composed of letters [‘mvsk’]; ‘m’ = mean, ‘v’ = variance, ‘s’ = Fisher’s skew and ‘k’ = Fisher’s kurtosis. (default = ‘mv’). Results : Levy-stable continuous random variable Code #1 : Creating Levy-stable Levy continuous random variable Python3 1== # importing library from scipy.stats import levy_stable numargs = levy_stable.numargs a, b = 4.32, 3.18 rv = levy_stable(a, b) print ("RV : \n", rv) Output : RV : scipy.stats._distn_infrastructure.rv_frozen object at 0x000002A9D6803648 Code #2 : Levy-stable continuous variates and probability distribution Python3 1== import numpy as np quantile = np.arange (0.03, 2, 0.21) # Random Variates R = levy_stable.rvs(1.8, -0.5, size = 10) print ("Random Variates : \n", R) # PDF R = levy_stable.pdf(a, b, quantile) print ("\nProbability Distribution : \n", R) Output : Random Variates : [ 1.20654126 -0.56381774 -1.31527459 -0.90027222 0.52535969 0.03076316 -4.69310302 0.61194358 1.31207992 -0.84552083] Probability Distribution : [nan nan nan nan nan nan nan nan nan nan] Code #3 : Graphical Representation. Python3 1== import numpy as np import matplotlib.pyplot as plt distribution = np.linspace(levy_stable.ppf(0.01, 1.8, -0.5), levy_stable.ppf(0.99, 1.8, -0.5), 100) print("Distribution : \n", distribution) Output : Distribution : [-4.92358285 -4.8368521 -4.75012136 -4.66339061 -4.57665986 -4.48992912 -4.40319837 -4.31646762 -4.22973687 -4.14300613 -4.05627538 -3.96954463 -3.88281389 -3.79608314 -3.70935239 -3.62262164 -3.5358909 -3.44916015 -3.3624294 -3.27569866 -3.18896791 -3.10223716 -3.01550641 -2.92877567 -2.84204492 -2.75531417 -2.66858343 -2.58185268 -2.49512193 -2.40839118 -2.32166044 -2.23492969 -2.14819894 -2.06146819 -1.97473745 -1.8880067 -1.80127595 -1.71454521 -1.62781446 -1.54108371 -1.45435296 -1.36762222 -1.28089147 -1.19416072 -1.10742998 -1.02069923 -0.93396848 -0.84723773 -0.76050699 -0.67377624 -0.58704549 -0.50031475 -0.413584 -0.32685325 -0.2401225 -0.15339176 -0.06666101 0.02006974 0.10680048 0.19353123 0.28026198 0.36699273 0.45372347 0.54045422 0.62718497 0.71391571 0.80064646 0.88737721 0.97410796 1.0608387 1.14756945 1.2343002 1.32103094 1.40776169 1.49449244 1.58122319 1.66795393 1.75468468 1.84141543 1.92814618 2.01487692 2.10160767 2.18833842 2.27506916 2.36179991 2.44853066 2.53526141 2.62199215 2.7087229 2.79545365 2.88218439 2.96891514 3.05564589 3.14237664 3.22910738 3.31583813 3.40256888 3.48929962 3.57603037 3.66276112] Comment More infoAdvertise with us Next Article Python - Rayleigh Distribution in Statistics M mathemagic Follow Improve Article Tags : Python Python scipy-stats-functions Practice Tags : python Similar Reads Python - Levy Distribution in Statistics scipy.stats.levy() is a levy continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x : quantiles loc : [opti 2 min read Python - Left-skewed Levy Distribution in Statistics scipy.stats.levy_l() is a left-skewed Levy continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x : quantil 2 min read Python - Mielke Distribution in Statistics scipy.stats.mielke() is a Mielke Beta-Kappa / Dagum continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x 2 min read Python - Rayleigh Distribution in Statistics scipy.stats.rayleigh() is a Rayleigh continuous random variable. As an instance of the rv_continuous class, the rayleigh object inherits from it a collection of generic methods and completes them with details specific to this particular distribution. Parameters: q : lower and upper tail probability 2 min read Python - Laplace Distribution in Statistics scipy.stats.laplace() is a Laplace continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x : quantiles loc : 2 min read Python - Skew-Normal Distribution in Statistics scipy.stats.skewnorm() is a skew-normal continuous random variable. It is inherited from the of generic methods as an instance of the rv_continuous class. It completes the methods with details specific for this particular distribution. Parameters : q : lower and upper tail probability x : quantiles 2 min read Like