The remarkable aspect of mainstream economists is their persistence treating values in (digital) ledgers as actual instances of banknotes (physical paper) as their mental model, then selectively dropping the model.
These are really good questions that actually would be best addressed by agent-based modeling, where individual agents (banks, employees, investors, bond traders, federal govt, state govt, firms etc) each have behaviors defined by rules and you run the system adjusting the rules to see how the scenario plays out. #julialang is a great tool for this using the Agents.jl library in part because it's fast
Uno de los libros más conocidos para aprender Julia es “Think Julia” de Ben Lauwens y Allen Downey.
Acabo de ver que existe una traducción llamada “Introducción a la Programación en Julia” traducida por Pamela Alejandra Bustamante Faúndez. Está disponible gratuitamente en:
(compared to python when it is forced to apply arbitrary functions with loops inside, element-wise to an array - that is, can't benefit from vectorised numpy functions)
this #maths experiment took about an hour in python and about 1 second in julia lang
sure my python isn't professional, but today was my first time with julia lang so that will be far from optimal either
hello #julialang people,
I am trying to add something to a package, so i opened the repl, entered pkg mode and ran develop MyPackage. Then I modified it in ~/.julia/dev/MyPackage but no changes showed up when I imported the package.
What did I do wrong
thanks