Department of Statistics
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- 2020
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Mark
Modeling asymmetry in volatility response - non-Gaussian innovations approach
(
- Master (One yr)
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Mark
Variable Selection for Estimating Optimal Sequential Treatment Decisions Using Bayesian Networks
(
- Master (Two yrs)
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Mark
Exploring the data behind students’ published theses - Analyzing the pride of Lund University
(
- Bach. Degree
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Mark
ATT PROGNOSTISERA DET FINANSIELLA RESULTATET I SVENSKA KOMMUNER EN JÄMFÖRELSE MELLAN ETT ELASTISKT NÄT OCH EN BASELINE
(
- Bach. Degree
-
Mark
Music Recommendations; Approximating user distributions to address the cold start problem
(
- Bach. Degree
- 2019
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Mark
Counterfactual Prediction Methods for Causal Inference in Observational Studies with Continuous Treatments
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- Master (One yr)
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Mark
Twitter bot detection & categorization - a comparative study of machine learning methods
(
- Master (One yr)
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Mark
A simple model of volatility in financial data - An alternative to GARCH models
(
- Master (One yr)
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Mark
Forecasting Election Results: A Bayesian Frequentist Comparison
(
- Bach. Degree
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Mark
Crime Prediction in Swedish Municipalities with machine learning algorithms
(
- Bach. Degree