StatsBase.jl
DSGE.jl
StatsBase.jl | DSGE.jl | |
---|---|---|
5 | 3 | |
565 | 842 | |
1.1% | 0.2% | |
6.5 | 2.4 | |
9 days ago | 28 days ago | |
Julia | Julia | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
StatsBase.jl
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Downloading packages to Julia 0.7
so finally I tried running Pkg.add(Pkg.PackageSpec(url="https://github.com/JuliaStats/StatsBase.jl", rev="v0.24.0")) but encountered an error saying in needed to download dependencies like DataStructures.
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R user excited about Julia
The author identified some bugs and those were fixed. But they were all edge cases or footguns that are obviously bad to do, but allowed because Julia is a flexible language. For example, in this issue, the author overwrites the array they are sampling from. Which is obviously going to produce bad results.
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Julia ranks in the top most loved programming languages for 2022
Well, out of the issues mentioned, the ones still open can be categorized as (1) aliasing problems with mutable vectors https://github.com/JuliaLang/julia/issues/39385 https://github.com/JuliaLang/julia/issues/39460 (2) not handling OffsetArrays correctly https://github.com/JuliaStats/StatsBase.jl/issues/646, https://github.com/JuliaStats/StatsBase.jl/issues/638, https://github.com/JuliaStats/Distributions.jl/issues/1265 https://github.com/JuliaStats/StatsBase.jl/issues/643 (3) bad interaction of buffering and I/O redirection https://github.com/JuliaLang/julia/issues/36069 (4) a type dispatch bug https://github.com/JuliaLang/julia/issues/41096
So if you avoid mutable vectors and OffsetArrays you should generally be fine.
As far as the argument "Julia is really buggy so it's unusable", I think this can be made for any language - e.g. rand is not random enough, Java's binary search algorithm had an overflow, etc. The fixed issues have tests added so they won't happen again. Maybe copying the test suites from libraries in other languages would have caught these issues earlier, but a new system will have more bugs than a mature system so some amount of bugginess is unavoidable.
- The Julia language has a number of correctness flaws
DSGE.jl
- Jdf.jl – Julia DataFrames serialization format
- [D] [R] Economics dissertation using Machine Learning
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Is the Fed New-Keynesian?
The thread https://news.ycombinator.com/item?id=31785199 Show HN: A central bank simulator game with a realistic economic model has attracted much interest.
This post is by a former University of Chicago macroeconomist and present Matlab for simulating the joint dynamics of interest rates, inflation, and unemployment. The author has other posts with Matlab code.
A macroeconomic model in Julia used by the New York Federal Reserve is at https://github.com/FRBNY-DSGE/DSGE.jl .
What are some alternatives?
Lux.jl - Explicitly Parameterized Neural Networks in Julia
GLM.jl - Generalized linear models in Julia
Petalisp - Elegant High Performance Computing
MixedModels.jl - A Julia package for fitting (statistical) mixed-effects models
Optimization.jl - Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.
ComponentArrays.jl - Arrays with arbitrarily nested named components.
Enzyme.jl - Julia bindings for the Enzyme automatic differentiator
ControlSystems.jl - A Control Systems Toolbox for Julia
diffrax - Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
ARCHModels.jl - A Julia package for estimating ARMA-GARCH models.
Distributions.jl - A Julia package for probability distributions and associated functions.
ScottishTaxBenefitModel.jl - A tax-benefit model for Scotland