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Quantitative Economics with Julia
Getting Started with Julia 1. Setting up Your Julia Environment 2. Introductory Examples 3. Julia Essentials 4. Arrays, Tuples, Ranges, and Other Fundamental Types 5. Introduction to Types and Generic Programming Package Ecosystem 6. Generic Programming 7. General Purpose Packages 8. Data and Statistics Packages 9. Solvers, Optimizers, and ...
Julia.quantecon.orgDA: 19 PA: 11 MOZ Rank: 30
64. About these Lectures — Quantitative Economics with …
64.2. Julia ¶. The coding language for this lecture series is Julia. Note that there’s also a related set of Python lectures. Python is a general purpose language featuring a huge user community in the sciences and an outstanding scientific and general ecosystem. Julia is a more focused language primarily used in technical and scientific ...
Julia.quantecon.orgDA: 19 PA: 20 MOZ Rank: 40
QuantEcon.jl – QuantEcon
More detailed instructions on setting up a Julia environment can be found on this page. Useful Links. Code library on GitHub; Documentation; Report an Issue; QuantEcon.jl is supported financially by the Alfred P. Sloan Foundation and is part of the QuantEcon organization.
Quantecon.orgDA: 13 PA: 14 MOZ Rank: 29
Quantitative Economics with Julia
Quantitative Economics with Python. This website presents a set of lectures on quantitative economic modeling, designed and written by Jesse Perla, Thomas J. Sargent and John Stachurski. The language instruction is Julia. This is one of a series of lectures by QuantEcon. Last compiled: 9 Apr 2022 ( view commits)
Preview.julia.quantecon.orgDA: 27 PA: 27 MOZ Rank: 31
QuantEcon
QuantEcon is a NumFOCUS fiscally sponsored project dedicated to development and documentation of modern open source computational tools for economics, econometrics, and decision making. We welcome contributions and collaboration from the economics community and other partner organizations.
Quantecon.orgDA: 13 PA: 13 MOZ Rank: 18
About – QuantEcon
About. QuantEcon is a nonprofit organization dedicated to improving economic modeling by enhancing computational tools for economists. Our activities include. developing and facilitating the development of open source software for economic modeling, and. building open, collaborative platforms for sharing, discussing and documenting open source ...
Quantecon.orgDA: 13 PA: 7 MOZ Rank: 25
QuantEcon · Julia Packages
Julia implementation of QuantEcon routines Author QuantEcon. Sub Category ECONOMETRICS. Website Github Popularity 375 Stars Updated Last 11 Months Ago Started In July 2014 Quantitative Economics (Julia) This repository collects code for quantitative economic modeling in Julia ...
Juliapackages.comDA: 17 PA: 12 MOZ Rank: 35
MATLAB–Python–Julia cheatsheet — Cheatsheets by QuantEcon …
MATLAB–Python–Julia cheatsheet. Dependencies and Setup. Creating Vectors. Creating Matrices. Manipulating Vectors and Matrices. Accessing Vector/Matrix Elements. Mathematical Operations. Sum / max / min. Programming.
Cheatsheets.quantecon.orgDA: 25 PA: 25 MOZ Rank: 33
Jupinx
Quantitative Economics with Julia; QuantEcon DataScience; Cheatsheets; Code. QuantEcon.py; QuantEcon.jl; Jupinx; Notebooks. NB Library; QE Notes; Community. Blog; Forum; Store; Repository; Twitter; Welcome to Jupinx, a build system for lectures. Jupinx is an open source tool for converting ReStructuredText source files into a website via Jupyter …
Jupinx.quantecon.orgDA: 20 PA: 20 MOZ Rank: 29
Quantitative Economics with Julia
This website presents a set of lectures on quantitative economic modeling, designed and written by Jesse Perla, Thomas J. Sargent and John Stachurski.
Preview.julia.quantecon.orgDA: 27 PA: 30 MOZ Rank: 66
Julia Lectures Updated – QuantEcon
Julia Lectures Updated. 8 Sep 2021. The Quantitative Economics with Julia lectures have been given a significant update.. Beyond infrastructure updates, the lecture notes now more strongly software engineering concepts, such source code control and collaboration and test-driven development and continuous integration.We see these as essential steps …
Quantecon.orgDA: 13 PA: 38 MOZ Rank: 61
QuantEcon – Notes
This notebook solves a sovereign default model using CUDA in Julia. Simulate a Cross-section Efficiently. Published a year ago by Julien Pascal in Julia 319 views. In this notebook, I describe Young's method (2010) to simulate a large number (infinity) of individuals efficiently. A brief note on Chebyshev approximation . Published 2 years ago by Mohammed Ait Lahcen in Python …
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Chapter 3 - Optimal Flows (Julia Code) — Economic Networks …
Here we demonstrate solving a shortest path problem using Bellman’s method. Our first step is to set up the cost function, which we store as an array called c. Note that we set c [i, j] = Inf when no edge exists from i to j. Next we define the Bellman operator. Now we arbitrarily set q ≡ 0, generate the sequence of iterates T q , T q 2, T q ...
Networks.quantecon.orgDA: 22 PA: 18 MOZ Rank: 52
QuantEcon · Julia Packages
One stop shop for the Julia package ecosystem. All Packages Trending Developers Categories ... QuantEcon.jl 375 Julia implementation of QuantEcon routines Games.jl 59 Algorithms and data structures for game theory in Julia CompEcon.jl 39 Julia versions of the CompEcon routines by Miranda and Fackler. ...
Juliapackages.comDA: 17 PA: 12 MOZ Rank: 42
3. Julia Essentials — Quantitative Economics with Julia
Getting Started with Julia 1. Setting up Your Julia Environment 2. Introductory Examples 3. Julia Essentials 4. Arrays, Tuples, Ranges, and Other Fundamental Types 5. Introduction to Types and Generic Programming Package Ecosystem 6. Generic Programming 7. General Purpose Packages 8. Data and Statistics Packages 9. Solvers, Optimizers, and ...
Julia.quantecon.orgDA: 19 PA: 44 MOZ Rank: 77
Getting Started · Distributions.jl - JuliaStats
Starting With a Normal Distribution. We start by drawing 100 observations from a standard-normal random variable. The first step is to set up the environment: julia> using Random, Distributions julia> Random.seed! ( 123) # Setting the seed. Then, we create a standard-normal distribution d and obtain samples using rand:
Juliastats.orgDA: 14 PA: 34 MOZ Rank: 63
Table of Contents – Quantitative Economics with Julia
This website presents a set of lectures on quantitative economic modeling, designed and written by Jesse Perla, Thomas J. Sargent and John Stachurski.
Preview.julia.quantecon.orgDA: 27 PA: 15 MOZ Rank: 58
QuantEcon/QuantEcon.jl: Julia implementation of QuantEcon …
Julia implementation of QuantEcon routines. Contribute to QuantEcon/QuantEcon.jl development by creating an account on GitHub.
Github.comDA: 10 PA: 23 MOZ Rank: 50
Troubleshooting – Quantitative Economics with Julia
To reset your whole lecture set, run rm -rf quantecon-notebooks-julia in the Terminal (after cd-ing to where they’re downloaded, which is usually the root) and click any lecture’s link again. Reporting an Issue¶ One way to give feedback is to raise an issue through our issue tracker. Please be as specific as possible. Tell us where the problem is and as much detail about your …
Preview.julia.quantecon.orgDA: 27 PA: 21 MOZ Rank: 66
GitHub - QuantEcon/lecture-julia.myst: Lecture source for …
Set the default interpreter for VS Code's Python extension to be the conda environment. Press <Ctrl-Shift-P> then Python: Select Interpreter. Choose the interpreter with lecture-julia.myst which should now be automatically activated in the terminal. If the interpreter does not show up in the drop-down, close and reopen VS Code, then try again.
Github.comDA: 10 PA: 29 MOZ Rank: 58
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