Reputation: 165
I want to use fsolve to solve for alpha and beta (from the Beta distribution)
import numpy as np
from scipy.optimize import fsolve
def mean_and_var(mu,sigma):
a, b = mu,*sigma
return (a/(a+b), a*b/(((a+b)**2)*(a+b+1)))
args = (.5,.05) #mean and variance
alpha,beta = fsolve( mean_and_var, 0, args )
#print (mean_and_var((a, b)))
This shoots me the error
TypeError: 'float' object is not iterable
Upvotes: 1
Views: 399
Reputation: 243897
When using fsolve you must modify the original equation to another one that has the form f(x)=0
, in your case:
mu=a/(a+b)
sigma=(ab)/((a+b)^2(a+b+1))
It becomes:
mu - a/(a+b) = 0
sigma - a*b/(((a+b)**2)*(a+b+1)) = 0
n the function that we pass the first parameter is the variable that one wants to find (a, b), and the second the other parameters (mu, sigma).
def mean_and_var(x, *args):
a, b = x
mu, sigma = args
eq1 = mu - a/(a+b)
eq2 = sigma - a*b/(((a+b)**2)*(a+b+1))
return eq1, eq2
args = (.5,.05)
a, b = fsolve(mean_and_var, (.1, .1), args=args)
print("solution: {}, {}".format(a, b))
print("eval in function: {}".format(mean_and_var((a, b), *args)))
output:
solution: 1.9999999999999376, 2.000000000000059
eval in function: (1.5154544286133387e-14, -4.163336342344337e-17)
Upvotes: 2