So I have one vector of alpha, one vector of beta, and I am trying to find a theta for when the sum of all the estimates (for alpha's 1 to N and beta's 1 to N) equals 60:

def CalcTheta(grensscore, alpha, beta):
theta = 0.0001
estimate = [grensscore-1]
while(sum(estimate) < grensscore):
theta += 0.00001
for x in range(len(beta)):
if x == 0:
estimate = []
estimate.append(math.exp(alpha[x] * (theta - beta[x])) /
(1 + math.exp(alpha[x] * (theta - beta[x]))))
return(theta)
Basically what I did is start from theta = 0.0001, and iterate through, calculating all these sums, and when it is lower than 60, continue by adding 0.0001 each time, while above 60 means we found the theta.
I found the value theta this way. Problem is, it took me about 60 seconds using Python, to find a theta of 0.456.
What is quicker approach to find this theta (since I would like to apply this for other data)?
If you know a lower and an upper bound for θ, and the function is monotonic in the range between these, then you could employ a bisection algorithm to easily and quickly find the desired value.
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