aishameriane
- B.Sc Statistics (100%) & Economics (100%) - M.Sc. in Economics (100%) - M.Phil. in Econometrics (100%) - Ph.D. in Econometrics (40%) - Cat lady (1000%)
Tinbergen Institute, Erasmus Universiteit Rotterdam & DNBRotterdam, NL
aishameriane's Stars
sktime/sktime
A unified framework for machine learning with time series
deedy/Deedy-Resume
A one page , two asymmetric column resume template in XeTeX that caters to an undergraduate Computer Science student
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
csev/py4e
Web site for www.py4e.com and source to the Python 3.0 textbook
matheusfacure/python-causality-handbook
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
paulgp/applied-methods-phd
Repo for Yale Applied Empirical Methods PHD Course
allisonhorst/stats-illustrations
R & stats illustrations by @allison_horst
uo-ec607/lectures
Lecture notes for EC 607
antontarasenko/awesome-economics
A curated collection of links for economists
FRBNY-DSGE/DSGE.jl
Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
OpenIntroStat/ims
đ Introduction to Modern Statistics - A college-level open-source textbook with a modern approach highlighting multivariable relationships and simulation-based inference. For v1, see https://openintro-ims.netlify.app.
BiomedSciAI/causallib
A Python package for modular causal inference analysis and model evaluations
udacity/sagemaker-deployment
Code and associated files for the deploying ML models within AWS SageMaker
econ-ark/HARK
Heterogenous Agents Resources & toolKit
shade-econ/sequence-jacobian
A unified framework to solve and analyze heterogeneous-agent macro models.
OU-PhD-Econometrics/fall-2020
gboehl/macro_puzzles
Collection of puzzles in macroeconomics
jesusfv/financial-frictions
Interactive guide to Fernåndez-Villaverde, Hurtado, and Nuño (2019): "Financial Frictions and the Wealth Distribution".
hblackburn/R4Econ
Shared resources for Econ Research Assistants working in R
jlukito/timeseries-bootcamp
SJMC Time Series Boot Camp - Materials by Josephine Lukito and Jordan Foley
CForg/Archive-of-Empirical-Dynamic-Programming-Research
Collection of published papers that estimate dynamic programming models
foundinblank/2019-ntid-data-workshop
NTID Reproducible Data Analysis Workshop (March 25-29 2019)
ProforTeam/profor
probability forecasting with macro variables
zschorli/Proehl_SolvingHeterogAgentModels
This is code for the working paper "Approximating Equilibria with Ex-Post Heterogeneity and Aggregate Risk" by Elisabeth Pröhl.
HoustonJ2013/LocalLinearForest
A python implementation of local linear forests (https://arxiv.org/pdf/1807.11408.pdf) based on sklearn
paeselhz/CepespVis
SubmissĂŁo para o 1Âș DESAFIO do CEPESP
EdsonCilos/mlcourse
RepositĂłrio para o curso de Machine Learning - prof. Edson Cilos Vargas JĂșnior.
zschorli/HARK
Heterogenous Agents Resources & toolKit
leilanefrc/intro-latex
Introdução ao LaTeX
NoFishLikeIan/fred_md
Import and transform the FRED monthly data.