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Ing. Michaela Kecskésová

Bachelor's thesis

Implementation of Sample Selection Estimators into Double Machine Learning Framework

Implementation of Sample Selection Estimators into Double Machine Learning Framework
Abstract:
Táto práca predstavuje tzv. dvojité strojové učenie (Double Machine Learning - DML), rámec navrhnutý na odhadovanie vektorov parametrov vo vysokodimenzionálnom prostredí, kde môže byť počet premenných potenciálne veľmi veľký. Okrem všeobecného popisu tohto rámca je hlavným cieľom práce implementovať nedávne rozšírenie DML do DoubleML, populárnej knižnice jazyka Python pre modely založené na DML, ktorej …more
Abstract:
This thesis presents an overview of Double Machine Learning (DML), a framework designed for estimating lower-dimensional parameter vectors in high-dimensional settings, where the number of variables can potentially be very large. In addition to outlining the general framework, the main goal of the thesis is to implement a recent extension of DML into DoubleML, a popular Python library for DML-based …more
 

Keywords

Double machine learning causal analysis econometrics sample selection DoubleML Python
 
Language used: English
Date on which the thesis was submitted / produced: 23. 5. 2024
Identifier: https://is.muni.cz/th/qqu9h/

Thesis defence

  • Date of defence: 24. 6. 2024
  • Supervisor: RNDr. Martin Jonáš, Ph.D.
  • Reader: RNDr. Vít Musil, Ph.D.

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