Sökning: "Estimator"

Visar resultat 1 - 5 av 324 uppsatser innehållade ordet Estimator.

1. 1. The Effects of Social Assistance and Unemployment Insurance on Employment Outcomes : Evidence from new micro level administrative data at Statistics Sweden

   Master-uppsats, Uppsala universitet/Nationalekonomiska institutionen

   Författare :Molly Bernhardsson; [2024]
   Nyckelord :Social assistance; Unemployment insurance; Employment outcomes; Propensity score matching; Kaplan-Meier estimator;

   Sammanfattning : In this study, I examine the employment effects on average earnings and duration to work during a 45 month period, after receiving social assistance (SA) in October 2019, compared to receiving unemployment insurance (UI) the same month. A distinction is made between two treatment groups; receiving SA in addition to UI (treatment I) and receiving SA (treatment II). LÄS MER

3. 2. The Effects of Social Assistance and Unemployment Insurance on Employment Outcomes : Evidence from new micro level administrative data at Statistics Sweden between 2019-2023

   Master-uppsats, Uppsala universitet/Nationalekonomiska institutionen

   Författare :Molly Bernhardsson; [2024]
   Nyckelord :Social assistance; Unemployment insurance; Employment outcomes; Propensity score matching; Kaplan-Meier estimator;

   Sammanfattning : In this study, I examine the employment effects on average earnings and duration to work during a 45 month period, after receiving social assistance (SA) in October 2019, compared to receiving unemployment insurance (UI) the same month. A distinction is made between two treatment groups; receiving SA in addition to UI (treatment I) and receiving SA (treatment II). LÄS MER

4. 3. Measuring the Utility of Synthetic Data : An Empirical Evaluation of Population Fidelity Measures as Indicators of Synthetic Data Utility in Classification Tasks

   Master-uppsats, Karlstads universitet/Institutionen för matematik och datavetenskap (from 2013)

   Författare :Alexander Florean; [2024]
   Nyckelord :Synthetic Data; Machine Learning; Population Fidelity Measures; Utility Metrics; Synthetic Data Quality Evaluation; Classification Algorithms; Utility Estimation; Data Privacy; Artificial Intelligence; Experiment Framework; Model Performance Assessment; Syntetisk Data; Maskininlärning; Population Fidelity Mätvärden; Användbarhetsmätvärden; Kvalitetsutvärdering av Syntetisk Data; Klassificeringsalgoritmer; Användbarhetsutvärdering; Dataintegritet; Artificiell Intelligens; AI; Experiment Ramverk; Utvärdering av Modellprestanda;

   Sammanfattning : In the era of data-driven decision-making and innovation, synthetic data serves as a promising tool that bridges the need for vast datasets in machine learning (ML) and the imperative necessity of data privacy. By simulating real-world data while preserving privacy, synthetic data generators have become more prevalent instruments in AI and ML development. LÄS MER

5. 4. Point process learning for non-parametric intensity estimation with focus on Voronoi estimation

   Master-uppsats, Göteborgs universitet/Institutionen för matematiska vetenskaper

   Författare :Alexander Thorén; [2023-03-28]
   Nyckelord :;

   Sammanfattning : Point process learning is a new statistical theory that gives us a way to estimate parameters using cross-validation for point processes. By thinning a point pattern we are able to create training and validation sets which are then used in prediction errors. LÄS MER

7. 5. Uncertainty Estimation in Radiation Dose Prediction U-Net

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Frida Skarf; [2023]
   Nyckelord :Radiation dose prediction models; U-net; quantile regression; Monte Carlo Dropout; epistemic uncertainty estimation; aleatoric uncertainty estimation; Stråldospredicerande modeller; U-net; kvantilregression; Monte Carlo Dropout; epistemisk osäkerhetsskattning; aletorisk osäkerhetsskattning;

   Sammanfattning : The ability to quantify uncertainties associated with neural network predictions is crucial when they are relied upon in decision-making processes, especially in safety-critical applications like radiation therapy. In this paper, a single-model estimator of both epistemic and aleatoric uncertainties in a regression 3D U-net used for radiation dose prediction is presented. LÄS MER