scipy stats.erlang() | Python Last Updated : 20 Mar, 2019 Comments Improve Suggest changes Like Article Like Report scipy.stats.erlang() : is an Erlang continuous random variable that is defined with a standard format and some shape parameters to complete its specification. it is a special case of the Gamma 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 : erlang continuous random variable Code #1 : Creating erlang continuous random variable Python3 from scipy.stats import erlang numargs = erlang.numargs [a] = [0.6, ] * numargs rv = erlang(a) print ("RV : \n", rv) Output : RV : <scipy.stats._distn_infrastructure.rv_frozen object at 0x0000018D544FBC88> Code #2 : erlang random variates and probability distribution. Python3 import numpy as np quantile = np.arange (0.01, 1, 0.1) # Random Variates R = erlang.rvs(a, scale = 2, size = 10) print ("Random Variates : \n", R) # PDF R = erlang.pdf(a, quantile, loc = 0, scale = 1) print ("\nProbability Distribution : \n", R) Output : Random Variates : [5.65708510e+00 5.16045580e+00 1.02056956e-01 3.64349340e-01 5.65593073e+00 2.27100280e+00 9.77623414e-04 2.01994399e-01 8.84331471e-01 2.20817630e+00] Probability Distribution : [0.01, 0.11, 0.21, 0.31, 0.41, 0.51, 0.61, 0.71, 0.81, 0.91] Code #3 : Graphical Representation. Python3 import numpy as np import matplotlib.pyplot as plt distribution = np.linspace(0, np.minimum(rv.dist.b, 5)) print("Distribution : \n", distribution) plot = plt.plot(distribution, rv.pdf(distribution)) Output : Distribution : Distribution : [0. 0.10204082 0.20408163 0.30612245 0.40816327 0.51020408 0.6122449 0.71428571 0.81632653 0.91836735 1.02040816 1.12244898 1.2244898 1.32653061 1.42857143 1.53061224 1.63265306 1.73469388 1.83673469 1.93877551 2.04081633 2.14285714 2.24489796 2.34693878 2.44897959 2.55102041 2.65306122 2.75510204 2.85714286 2.95918367 3.06122449 3.16326531 3.26530612 3.36734694 3.46938776 3.57142857 3.67346939 3.7755102 3.87755102 3.97959184 4.08163265 4.18367347 4.28571429 4.3877551 4.48979592 4.59183673 4.69387755 4.79591837 4.89795918 5. ] Code #4 : Varying Positional Arguments Python3 import matplotlib.pyplot as plt import numpy as np x = np.linspace(0, 5, 100) # Varying positional arguments y1 = erlang.pdf(x, 2, 6) y2 = erlang.pdf(x, 1, 4) plt.plot(x, y1, "*", x, y2, "r--") Output : Comment More infoAdvertise with us Next Article scipy stats.erlang() | Python V vishal3096 Follow Improve Article Tags : Python Python-scipy Python scipy-stats-functions Practice Tags : python Similar Reads scipy.stats.expon() | Python scipy.stats.expon() is an exponential continuous random variable that is defined with a standard format and some shape parameters to complete its specification. 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