We read every piece of feedback, and take your input very seriously.
To see all available qualifiers, see our documentation.
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
I can't find a proper documentation (aside the github repository redme) neither in SymEngine.jl neither in the symengine C++ repository..
The text was updated successfully, but these errors were encountered:
It seems very close to SymPy. For now I can't find equivalent of simplify() and solve():
An example to symbolically compute a Maximum Likelihood Estimator that resembles very much SymPy.jl:
using SymEngine @vars Σx² θ n x # MLE for Normal(0,θ) Lakn = (1/(SymEngine.sqrt(2*SymEngine.pi * θ)^n) ) * exp(-Σx² / (2*θ)) lLn = log(Lakn) # Error: dlL1_θ = SymEngine.simplify(diff(lLn,θ)) dlL1_θ = diff(lLn,θ) # Error: SymEngine.solve(dlL1_θ,θ) L1 = (1/(SymEngine.sqrt(2*SymEngine.pi * θ)) ) * exp(-x^2 / (2*θ)) lL1 = (log(L1)) dlL1_θ = (diff(lL1,θ)) dlL2_θ = (diff(dlL1_θ,θ)) E = subs(dlL2_θ , x^2=>θ) Ifisher = -E Varθ = 1/Ifisher
Sorry, something went wrong.
Documentation is now available. https://symengine.org/SymEngine.jl/
No branches or pull requests
I can't find a proper documentation (aside the github repository redme) neither in SymEngine.jl neither in the symengine C++ repository..
The text was updated successfully, but these errors were encountered: