sympy.stats.Moyal() in python
With the help of sympy.stats.Moyal()
method, we can get the continuous random variable which represents the moyal distribution.
Syntax :
sympy.stats.Moyal(name, mu, sigma)
Where, mu and sigma are real number.
Return : Return the continuous random variable.
Example #1 :
In this example we can see that by using sympy.stats.Moyal()
method, we are able to get the continuous random variable representing moyal distribution by using this method.
# Import sympy and Moyal from sympy.stats import Moyal, density from sympy import Symbol, pprint z = Symbol( "z" ) mu = Symbol( "mu" , positive = True ) sigma = Symbol( "sigma" , positive = True ) # Using sympy.stats.Moyal() method X = Moyal( "x" , mu, sigma) gfg = density(X)(z) print (gfg) |
Output :
sqrt(2)*exp(-exp((mu – z)/sigma)/2 – (-mu + z)/(2*sigma))/(2*sqrt(pi)*sigma)
Example #2 :
# Import sympy and Moyal from sympy.stats import Moyal, density, cdf from sympy import Symbol, pprint z = Symbol( "z" ) mu = Symbol( "mu" , positive = True ) sigma = Symbol( "sigma" , positive = True ) # Using sympy.stats.Moyal() method X = Moyal( "x" , mu, sigma) Z = density(X)(z) gfg = simplify(cdf(X)(z)) print (gfg) |
Output :
1 – erf(sqrt(2)*exp((mu – z)/(2*sigma))/2)
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